DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Remarks page 15-19, Applicant contends:
The claims do not “recite” the rejection’s alleged exception.
Response:
The claims are interpreted as involving the abstract ideas more than simple involvement. Claims, like claim 18, note “determining a contribution degree of a first factor of the plurality of factors to target observed data of the target factor based on the causal structure and the observed data corresponding to the plurality of factors”. The idea of determining something, such as a contribution degree, very much aligns with the idea of a mental process.
MPEP 2106.04(Section 3): "The courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, "methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’" 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)). See also Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 (2012) ("‘[M]ental processes[] and abstract intellectual concepts are not patentable, as they are the basic tools of scientific and technological work’" (quoting Benson, 409 U.S. at 67, 175 USPQ at 675)); Parker v. Flook, 437 U.S. 584, 589, 198 USPQ 193, 197 (1978) (same)."
The BRI of the claim is seen as reasonable, for while the specification may not note elements could be performed in the human mind, the specification does not have to note such things for the claims to be interpreted as such. As noted in the MPEP, BRI is done with the broadest reasonable interpretation of what the claims read in order to give a claim the best chance after prosecution.
MPEP 2111: "Because applicant has the opportunity to amend the claims during prosecution, giving a claim its broadest reasonable interpretation will reduce the possibility that the claim, once issued, will be interpreted more broadly than is justified. In re Yamamoto, 740 F.2d 1569, 1571 (Fed. Cir. 1984); In re Zletz, 893 F.2d 319, 321, 13 USPQ2d 1320, 1322 (Fed. Cir. 1989) ('During patent examination the pending claims must be interpreted as broadly as their terms reasonably allow.')"
The interpretation of the claims having abstract ideas is determined to be reasonable, for the wording of the claims appears to be directed towards ideas that fit within the bounds of elements such as mental processes and the wording of the claims is broad enough to enable the BRI given.
Remarks pages 19-21, Applicant contends:
The claims, previously or at least as currently pending, reflect a “particular solution”.
Response:
In regards to amended limitations, Applicant’s arguments with respect to claim(s) 18 and analogous have been considered but are moot because the new ground of rejection contain elements that have not been previously examined or does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
In regards to existing limitations, the existing limitations are not particular, as the elements are forms of mere data gathering and an abstract idea (at least for claim 18). Abstract ideas cannot integrate into a practical application
(MPEP 2106.05(a): "It is important to note, the judicial exception alone cannot provide the improvement. The improvement can be provided by one or more additional elements. See the discussion of Diamond v. Diehr, 450 U.S. 175, 187 and 191-92, 209 USPQ 1, 10 (1981)) in subsection II, below. In addition, the improvement can be provided by the additional element(s) in combination with the recited judicial exception. See MPEP § 2106.04(d) (discussing Finjan, Inc. v. Blue Coat Sys., Inc., 879 F.3d 1299, 1303-04, 125 USPQ2d 1282, 1285-87 (Fed. Cir. 2018)). Thus, it is important for examiners to analyze the claim as a whole when determining whether the claim provides an improvement to the functioning of computers or an improvement to other technology or technical field.")
and gathering or transmitting data is not seen as integrating into a practical application (see MPEP 2106.05(d) example i in computer functions). Since no “particular” solution or method appears presented in the claims, the claims are not deemed reflecting a “particular solution”.
Remarks page 22, Applicant contends:
“Because the Applicant presents at least as much reasoning that the claims should be found patent eligible as the rejection presents to the contrary, the rejection should not be considered to be “more likely than not” appropriate and should therefore not be made as noted at page 5 of the memorandum referenced above.”
Response:
The current arguments presented were not seen as convincing, as a result, equal or greater reasoning for allowable under 101 is not seen as present. Meaning the evidence provided by the MPEP in regards to the rejections made under 101, as well as the arguments made in favor of keeping the 101s noted earlier in the responses, are seen as providing “more likely than not” evidence of a rejection under 101.
In regards to possible methods of overcoming the 101 rejections, some ideas might be useful in consideration. The manipulation of data, such as finding correlations, causations, change rates, etc. have difficultly integrating abstract ideas into practical applications by themselves as no system seems improved or changed as a result of the data. Utilizing the data in some way, especially when noted in a particular manner, can result in a limitation that is not merely a recitation of “apply it”, thus possible capable of integrating into a practical application and satisfying requirements under 101. The current specification notes possible uses of the data found or created in the claims ([Current Application 0002]: “For example, in the retail field, the result of causal discovery can be used to assist in establishing various sales policies; in the medical and health field, the result of causal discovery can be used to assist in establishing treatment plans for patients, and so on.”). Having a particular way or method noted for the data to be used to “assist in establishing various sales policies” or such could be a form of limitation that does more than mere “apply it”. No clear wording can be given on how broad of a limitation would still be more than mere “apply it” without direct analysis of the limitation itself, thus what could be amended into the claims is left to the applicant to decide.
Remarks pages 22-24, Applicant contends:
The current presented prior art does not teach all of the elements of the amended claims.
Response:
In regards to amended limitations, Applicant’s arguments with respect to claim(s) 18 and analogous have been considered but are moot because the new ground of rejection contain elements that have not been previously examined or does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Claim Objections
Claims 18, 32, and 37 objected to because of the following informalities: Claim 18 recites a list “based on the target factor being the blood pressure of the patient, heart rates, cardiac outputs, allergy indicators, total peripheral vascular resistance, catecholamine release, and blood pressure” which recites “blood pressure” twice. Appropriate correction is required. Removal of one of the recitations of blood pressure could help address the duplicate recitation.
Claim Rejections - 35 USC § 112
Regarding 112(b):
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 18-37 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
In regard to Claim 18:
Claim 18 recites the limitation "and the target factor being any of customer satisfaction with telecom operators, a blood pressure of a patient, sales of a target commodity, and software development" as well as “and the target observed data comprising: based on the target factor being of the customer satisfaction with telecom operators, customer consumption behavior data comprising an age of a customer, a monthly consumption of an Internet traffic, a ratio of free traffic, and a total monthly consumption of a plurality of Internet traffics including the Internet traffic”. There is insufficient antecedent basis for this limitation in the claim. The first recitation indicates that the target factor could any one of the listed options, but later in the “target observed data comprising: based on the target factor being…” the target factor is noted as being a list of things where the lists would even contain elements that are not included in this limitation. As a result one cannot determine which limitation to follow (such as whether the target factor is one thing or many things or is limited by the first list or the second list) thus leaving the claim indefinite.
The “target observed data” is “of the target factor” is noted in claim 18. That makes the “based on the target factor being…” in “the target observed data comprising” create confusion, as that indicates the target observed data comprises the target factor where the target factor is some items, but the target observed data is noted as being an element of the target factor. This creates a 112(b) antecedent issue of not being able to tell what the target observed data is supposed to be. “the target observed data comprising: based on…” adds confusion, for how does the target observed data comprise “based on” something is not understood.
In regards to claims 32 and 37:
Claims 32 and 37 are analogous to claim 18 and thus recite the same 112(b) rejections as claim 18.
In regards to dependent claims:
Dependent claims of claims rejected under 112(b) are also rejected for being dependent upon a rejected claim.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 18-37 are rejected under 35 U.S.C. 101 because the claimed invention is directed towards an abstract idea without significantly more.
In regards to Claim 18:
Step 1: Is the claim directed towards a process, machine, manufacture, or composition of matter?
Yes, it is directed towards a method, so a process.
Step 2A Prong 1: Does the claim recite a law of nature, a natural phenomenon, or an abstract idea?
Yes, the claim does recite a(n) abstract idea.
Claim 18 recites the following abstract ideas:
determining a contribution degree of a first factor of the plurality of factors to target observed data of the target factor based on the causal structure and the observed data corresponding to the plurality of factors
This limitation is directed towards the abstract idea of a mental process, or a concept performed in the human mind, including observation, evaluation, judgement or opinion (see MPEP 2106.04(a)(2) subsection 3). Here it is seen as evaluation.
Step 2A Prong 2: Does the claim recite additional elements that integrate the exception into a practical application of the exception?
No, the application does not recite any additional elements that would integrate the abstract idea into a practical application.
Claim 18 recites the following additional elements:
obtaining observed data corresponding to a plurality of factors to be analyzed
This limitation is directed towards the insignificant extra solution activity of mere data gathering (see MPEP § 2106.05(g)).
in response to one of the plurality of factors being selected as a target factor, obtaining a causal structure of the plurality of factors, the causal structure indicating causal relationships between the plurality of factors
This limitation is directed towards the insignificant extra solution activity of mere data gathering (see MPEP § 2106.05(g)).
and the target factor being any of customer satisfaction with telecom operators, a blood pressure of a patient, sales of a target commodity, and software development
This limitation is directed towards linking or indicating a field of use or technological environment (see MPEP 2106.05(h)).
and the target observed data comprising: based on the target factor being of the customer satisfaction with telecom operators, customer consumption behavior data comprising an age of a customer, a monthly consumption of an Internet traffic, a ratio of free traffic, and a total monthly consumption of a plurality of Internet traffics including the Internet traffic, based on the target factor being the blood pressure of the patient, heart rates, cardiac outputs, allergy indicators, total peripheral vascular resistance, catecholamine release, and blood pressure , based on the target factor being sales of the target commodity, commodity promotion investment, commodity display investment, sales staff investment, advertising investment, and new commodity marketing investment, and based on the target factor being software development, development cycle, resources invested in development, a software architecture method, a number of software architecture levels, a code length, a number of functions, a programming language, a number of modules, a failure rate of unit testing, a failure rate of block box testing, a failure rate of white box testing, and a failure rate of a running stage
This limitation is directed towards linking or indicating a field of use or technological environment (see MPEP 2106.05(h)).
Step 2B: Does the claim as a whole amount to significantly more than the judicial exception?
No, the claim as a whole does not amount to significantly more than the judicial exception. All elements of the claim, viewed individually or wholistically, do not provide an inventive concept or otherwise significantly more than the abstract idea itself.
Claim 18 recites the following additional elements:
obtaining observed data corresponding to a plurality of factors to be analyzed
This limitation is directed towards the insignificant extra solution activity of mere data gathering (see MPEP § 2106.05(g)). This is a well understood, routine, conventional activity of transmitting data (see MPEP 2106.05(d) example i in computer functions).
in response to one of the plurality of factors being selected as a target factor, obtaining a causal structure of the plurality of factors, the causal structure indicating causal relationships between the plurality of factors
This limitation is directed towards the insignificant extra solution activity of mere data gathering (see MPEP § 2106.05(g)). This is a well understood, routine, conventional activity of transmitting data (see MPEP 2106.05(d) example i in computer functions).
and the target factor being any of customer satisfaction with telecom operators, a blood pressure of a patient, sales of a target commodity, and software development
This limitation is directed towards linking or indicating a field of use or technological environment (see MPEP 2106.05(h)). Limitations that amount to merely linking/indicating to a field of use or technological environment, such having the data be related to field like power/electricity (see MPEP 2106.05(h)(vi)), do not amount to significantly more than the exception itself.
and the target observed data comprising: based on the target factor being of the customer satisfaction with telecom operators, customer consumption behavior data comprising an age of a customer, a monthly consumption of an Internet traffic, a ratio of free traffic, and a total monthly consumption of a plurality of Internet traffics including the Internet traffic, based on the target factor being the blood pressure of the patient, heart rates, cardiac outputs, allergy indicators, total peripheral vascular resistance, catecholamine release, and blood pressure , based on the target factor being sales of the target commodity, commodity promotion investment, commodity display investment, sales staff investment, advertising investment, and new commodity marketing investment, and based on the target factor being software development, development cycle, resources invested in development, a software architecture method, a number of software architecture levels, a code length, a number of functions, a programming language, a number of modules, a failure rate of unit testing, a failure rate of block box testing, a failure rate of white box testing, and a failure rate of a running stage
This limitation is directed towards linking or indicating a field of use or technological environment (see MPEP 2106.05(h)). Limitations that amount to merely linking/indicating to a field of use or technological environment, such having the data be related to field like power/electricity (see MPEP 2106.05(h)(vi)), do not amount to significantly more than the exception itself.
In regards to claim 19:
Step 2A Prong 2: Does the claim recite additional elements that integrate the exception into a practical application of the exception?
No, the application does not recite any additional elements that would integrate the abstract idea into a practical application.
Claim 19 recites the following additional elements:
receiving a first user input specifying the observed data corresponding to the plurality of factors
This limitation is directed towards the insignificant extra solution activity of mere data gathering (see MPEP § 2106.05(g)).
Step 2B: Does the claim as a whole amount to significantly more than the judicial exception?
No, the claim as a whole does not amount to significantly more than the judicial exception. All elements of the claim, viewed individually or wholistically, do not provide an inventive concept or otherwise significantly more than the abstract idea itself.
Claim 19 recites the following additional elements:
receiving a first user input specifying the observed data corresponding to the plurality of factors
This limitation is directed towards the insignificant extra solution activity of mere data gathering (see MPEP § 2106.05(g)). This is a well understood, routine, conventional activity of transmitting data (see MPEP 2106.05(d) example i in computer functions).
In regards to Claim 20:
Step 2A Prong 1: Does the claim recite a law of nature, a natural phenomenon, or an abstract idea?
Yes, the claim does recite a(n) abstract idea.
Claim 20 recites the following abstract ideas:
in accordance with a determination that the type of analysis is a type of average analysis, averaging the plurality of data items of each of the plurality of factors to determine observed data of the factor
This limitation is directed towards the abstract idea of a mental process, or a concept performed in the human mind, including observation, evaluation, judgement or opinion (see MPEP 2106.04(a)(2) subsection 3). Here it is seen as evaluation and judgement.
in accordance with a determination that the type of analysis is a type of summing analysis, aggregating the plurality of data items of each of the plurality of factors to determine observed data of the factor
This limitation is directed towards the abstract idea of a mental process, or a concept performed in the human mind, including observation, evaluation, judgement or opinion (see MPEP 2106.04(a)(2) subsection 3). Here it is seen as evaluation and judgement.
Step 2A Prong 2: Does the claim recite additional elements that integrate the exception into a practical application of the exception?
No, the application does not recite any additional elements that would integrate the abstract idea into a practical application.
Claim 20 recites the following additional elements:
receiving a second user input specifying a type of analysis and a plurality of data items of each of the plurality of factors within a plurality of time ranges
This limitation is directed towards the insignificant extra solution activity of mere data gathering (see MPEP § 2106.05(g)).
Step 2B: Does the claim as a whole amount to significantly more than the judicial exception?
No, the claim as a whole does not amount to significantly more than the judicial exception. All elements of the claim, viewed individually or wholistically, do not provide an inventive concept or otherwise significantly more than the abstract idea itself.
Claim 20 recites the following additional elements:
receiving a second user input specifying a type of analysis and a plurality of data items of each of the plurality of factors within a plurality of time ranges
This limitation is directed towards the insignificant extra solution activity of mere data gathering (see MPEP § 2106.05(g)). This is a well understood, routine, conventional activity of transmitting data (see MPEP 2106.05(d) example i in computer functions).
In regards to Claim 21:
Step 2A Prong 2: Does the claim recite additional elements that integrate the exception into a practical application of the exception?
No, the application does not recite any additional elements that would integrate the abstract idea into a practical application.
Claim 21 recites the following additional elements:
receiving a third user input specifying the target factor
This limitation is directed towards the insignificant extra solution activity of mere data gathering (see MPEP § 2106.05(g)).
Step 2B: Does the claim as a whole amount to significantly more than the judicial exception?
No, the claim as a whole does not amount to significantly more than the judicial exception. All elements of the claim, viewed individually or wholistically, do not provide an inventive concept or otherwise significantly more than the abstract idea itself.
Claim 21 recites the following additional elements:
receiving a third user input specifying the target factor
This limitation is directed towards the insignificant extra solution activity of mere data gathering (see MPEP § 2106.05(g)). This is a well understood, routine, conventional activity of transmitting data (see MPEP 2106.05(d) example i in computer functions).
In regards to Claim 22:
Step 2A Prong 1: Does the claim recite a law of nature, a natural phenomenon, or an abstract idea?
Yes, the claim does recite a(n) abstract idea.
Claim 22 recites the following abstract ideas:
determining at least one of a base contribution degree of the first factor to the target observed data independently of other factors among the plurality of factors, a total contribution degree of the first factor to the target observed data, the total contribution degree indicating a total sum of contribution degrees of the first factor to the target observed data and at least one second factor of the plurality of factors to the target observed data via the first factor, and a relational contribution degree of a causal relationship between the first factor and a third factor of the plurality of factors to the target observed data
This limitation is directed towards the abstract idea of a mental process, or a concept performed in the human mind, including observation, evaluation, judgement or opinion (see MPEP 2106.04(a)(2) subsection 3). Here it is seen as evaluationt.
In regards to Claim 23:
Step 2A Prong 2: Does the claim recite additional elements that integrate the exception into a practical application of the exception?
No, the application does not recite any additional elements that would integrate the abstract idea into a practical application.
Claim 23 recites the following additional elements:
presenting the contribution degree of the first factor to the target observed data to a user by at least one of: presenting the contribution degree in association with the causal structure, presenting the contribution degree in association with the target observed data, and separately presenting the contribution degree
This limitation is directed towards the insignificant extra solution activity of mere data gathering (see MPEP § 2106.05(g)).
Step 2B: Does the claim as a whole amount to significantly more than the judicial exception?
No, the claim as a whole does not amount to significantly more than the judicial exception. All elements of the claim, viewed individually or wholistically, do not provide an inventive concept or otherwise significantly more than the abstract idea itself.
Claim 23 recites the following additional elements:
presenting the contribution degree of the first factor to the target observed data to a user by at least one of: presenting the contribution degree in association with the causal structure, presenting the contribution degree in association with the target observed data, and separately presenting the contribution degree
This limitation is directed towards the insignificant extra solution activity of mere data gathering (see MPEP § 2106.05(g)). This is a well understood, routine, conventional activity of transmitting data (see MPEP 2106.05(d) example i in computer functions).
In regards to Claim 24:
Step 2A Prong 1: Does the claim recite a law of nature, a natural phenomenon, or an abstract idea?
Yes, the claim does recite a(n) abstract idea.
Claim 24 recites the following abstract ideas:
determining base data of the first factor based on the observed data of the plurality of factors and the causal structure, the base data of the first factor indicating a portion of the observed data of the first factor that is not affected by other factors among the plurality of factors
This limitation is directed towards the abstract idea of a mental process, or a concept performed in the human mind, including observation, evaluation, judgement or opinion (see MPEP 2106.04(a)(2) subsection 3). Here it is seen as evaluation.
in accordance with a determination that the first factor is not the target factor, determining a change rate of the target factor with respect to the first factor based on a causal relationship between the first factor and the target factor as indicated by the causal structure
This limitation is directed towards the abstract idea of a mental process, or a concept performed in the human mind, including observation, evaluation, judgement or opinion (see MPEP 2106.04(a)(2) subsection 3). Here it is seen as evaluation and judgement.
determining the base contribution degree of the first factor to the target observed data based on the base data of the first factor and the change rate of the target factor with respect to the first factor
This limitation is directed towards the abstract idea of a mental process, or a concept performed in the human mind, including observation, evaluation, judgement or opinion (see MPEP 2106.04(a)(2) subsection 3). Here it is seen as evaluation.
in accordance with a determination that the first factor is the target factor, determining the base data of the first factor as the base contribution degree of the first factor to the target observed data
This limitation is directed towards the abstract idea of a mental process, or a concept performed in the human mind, including observation, evaluation, judgement or opinion (see MPEP 2106.04(a)(2) subsection 3). Here it is seen as evaluation and judgement.
In regards to Claim 25:
Step 2A Prong 1: Does the claim recite a law of nature, a natural phenomenon, or an abstract idea?
Yes, the claim does recite a(n) abstract idea.
Claim 25 recites the following abstract ideas:
wherein the causal structure is indicated by a causal graph comprising a plurality of nodes that represent the plurality of factors and edges that connect the plurality of nodes, and an edge directly connecting a pair of nodes among the plurality of nodes represents a direct causal relationship between a pair of factors corresponding to the pair of nodes
This limitation is directed towards the continuation abstract idea of a mental process, or a concept performed in the human mind, including observation, evaluation, judgement or opinion (see MPEP 2106.04(a)(2) subsection 3). Here it is seen as a continuation of the abstract ideas from claim 18 using the causal structure.
wherein determining the change rate of the target factor with respect to the first factor comprises: determining, from the causal graph, at least one path from the first factor to the target factor, each of the at least one path comprising at least one edge in the causal graph
This limitation is directed towards the abstract idea of a mental process, or a concept performed in the human mind, including observation, evaluation, judgement or opinion (see MPEP 2106.04(a)(2) subsection 3). Here it is seen as evaluation.
determining a partial change rate of the target factor with respect to the first factor on the path based on a direct change rate of an effect factor with respect to a cause factor in a direct causal relationship represented by at least one edge included in the path
This limitation is directed towards the abstract idea of a mental process, or a concept performed in the human mind, including observation, evaluation, judgement or opinion (see MPEP 2106.04(a)(2) subsection 3). Here it is seen as evaluation.
determining a change rate of the target factor with respect to the first factor based on a sum of at least one partial change rate determined for the at least one path
This limitation is directed towards the abstract idea of a mental process, or a concept performed in the human mind, including observation, evaluation, judgement or opinion (see MPEP 2106.04(a)(2) subsection 3). Here it is seen as evaluation.
Step 2A Prong 2: Does the claim recite additional elements that integrate the exception into a practical application of the exception?
No, the application does not recite any additional elements that would integrate the abstract idea into a practical application.
Claim 25 recites the following additional elements:
for each of the at least one path
This limitation is directed towards the insignificant extra solution activity of repetitive calculations (see MPEP § 2106.05(d)).
Step 2B: Does the claim as a whole amount to significantly more than the judicial exception?
No, the claim as a whole does not amount to significantly more than the judicial exception. All elements of the claim, viewed individually or wholistically, do not provide an inventive concept or otherwise significantly more than the abstract idea itself.
Claim 25 recites the following additional elements:
for each of the at least one path
This limitation is directed towards the insignificant extra solution activity of repetitive calculations (see MPEP § 2106.05(d)). Repetitive calculations are considered a well understood, routine, and conventional activity acknowledged by the courts (see MPEP § 2106.05(d) subsection 2 example 2 for a computer).
In regards to Claim 26:
Step 2A Prong 1: Does the claim recite a law of nature, a natural phenomenon, or an abstract idea?
Yes, the claim does recite a(n) abstract idea.
Claim 26 recites the following abstract ideas:
in accordance with a determination that the causal structure indicates that the plurality of factors comprise at least one factor as a direct cause of the first cause, determining, from a direct causal relationship between the at least one factor and the first factor as indicated by the causal structure, at least one direct change rate of the first factor with respect to the at least one factor
This limitation is directed towards the abstract idea of a mental process, or a concept performed in the human mind, including observation, evaluation, judgement or opinion (see MPEP 2106.04(a)(2) subsection 3). Here it is seen as evaluation and judgement.
determining base data of the first factor based on observed data of the first factor and the at least one factor and the at least one determined direct change rate
This limitation is directed towards the abstract idea of a mental process, or a concept performed in the human mind, including observation, evaluation, judgement or opinion (see MPEP 2106.04(a)(2) subsection 3). Here it is seen as evaluation.
in accordance with a determination that the causal structure indicates that the plurality of factors comprise no factor as a direct cause of the first factor, determining observed data of the first factor as base data of the first factor
This limitation is directed towards the abstract idea of a mental process, or a concept performed in the human mind, including observation, evaluation, judgement or opinion (see MPEP 2106.04(a)(2) subsection 3). Here it is seen as evaluation and judgement.
In regards to Claim 27:
Step 2A Prong 1: Does the claim recite a law of nature, a natural phenomenon, or an abstract idea?
Yes, the claim does recite a(n) abstract idea.
Claim 27 recites the following abstract ideas:
wherein the causal structure indicates that the at least one second factor is a direct cause of the first factor, and determining the total contribution degree of the first factor to the target observed data comprises: determining at least one relational contribution degree of a direct causal relationship between the at least one second factor and the first factor to the target observed data
This limitation is directed towards the abstract idea of a mental process, or a concept performed in the human mind, including observation, evaluation, judgement or opinion (see MPEP 2106.04(a)(2) subsection 3). Here it is seen as evaluation and judgement.
determining a base contribution degree of the first factor to the target observed data
This limitation is directed towards the abstract idea of a mental process, or a concept performed in the human mind, including observation, evaluation, judgement or opinion (see MPEP 2106.04(a)(2) subsection 3). Here it is seen as evaluation.
determining the total contribution degree of the first factor to the target observed data based on a sum of the base contribution degree of the first factor to the target observed data and the at least one relational contribution degree
This limitation is directed towards the abstract idea of a mental process, or a concept performed in the human mind, including observation, evaluation, judgement or opinion (see MPEP 2106.04(a)(2) subsection 3). Here it is seen as evaluation.
In regards to Claim 28:
Step 2A Prong 1: Does the claim recite a law of nature, a natural phenomenon, or an abstract idea?
Yes, the claim does recite a(n) abstract idea.
Claim 28 recites the following abstract ideas:
wherein the causal structure indicates that the first factor is a cause of the third factor, and determining the relational contribution degree of the causal relationship between the first factor and the third factor to the target observed data comprises: determining a base contribution degree and a total contribution degree of the third factor to the target observed data
This limitation is directed towards the abstract idea of a mental process, or a concept performed in the human mind, including observation, evaluation, judgement or opinion (see MPEP 2106.04(a)(2) subsection 3). Here it is seen as evaluation and judgement.
determining a change rate of the target factor with respect to the third factor based on a causal relationship between the third factor and the target factor as indicated by the causal structure
This limitation is directed towards the abstract idea of a mental process, or a concept performed in the human mind, including observation, evaluation, judgement or opinion (see MPEP 2106.04(a)(2) subsection 3). Here it is seen as evaluation.
in accordance with a determination that the causal structure indicates that the first factor is an only cause of the third factor, determining a difference between the total contribution degree and the base contribution degree of the third factor as the relational contribution degree of the causal relationship between the first factor and the third factor to the target observed data
This limitation is directed towards the abstract idea of a mental process, or a concept performed in the human mind, including observation, evaluation, judgement or opinion (see MPEP 2106.04(a)(2) subsection 3). Here it is seen as evaluation and judgement.
In regards to Claim 29:
Step 2A Prong 1: Does the claim recite a law of nature, a natural phenomenon, or an abstract idea?
Yes, the claim does recite a(n) abstract idea.
Claim 29 recites the following abstract ideas:
in accordance with a determination that the causal structure indicates that at least one fourth factor is a further cause of the third factor, determining, based on the causal structure, a further relational contribution degree of a causal relationship between the at least one fourth factor and the third factor to the target observed data
This limitation is directed towards the abstract idea of a mental process, or a concept performed in the human mind, including observation, evaluation, judgement or opinion (see MPEP 2106.04(a)(2) subsection 3). Here it is seen as evaluation and judgement.
determining the relational contribution degree of the causal relationship between the first factor and the third factor to the target observed data by subtracting a sum of the further relational contribution degree and the base contribution degree of the third factor to the target observed data from the total contribution degree of the third factor to the target observed data
This limitation is directed towards the abstract idea of a mathematical concept (see MPEP 2106.04(a)(2) subsection 1).
In regards to Claim 30:
Step 2A Prong 1: Does the claim recite a law of nature, a natural phenomenon, or an abstract idea?
Yes, the claim does recite a(n) abstract idea.
Claim 30 recites the following abstract ideas:
wherein the causal structure indicates that the first factor is a cause of the third factor, and determining the relational contribution degree of the causal relationship between the first factor and the third factor to the target observed data comprises: determining a first change rate of the third factor with respect to the first factor from a causal relationship between the first factor and the third factor as indicated by the causal structure
This limitation is directed towards the abstract idea of a mental process, or a concept performed in the human mind, including observation, evaluation, judgement or opinion (see MPEP 2106.04(a)(2) subsection 3). Here it is seen as evaluation and judgement.
determining a second change rate of the target factor with respect to the third factor from a causal relationship between the third factor and the target factor as indicated by the causal structure
This limitation is directed towards the abstract idea of a mental process, or a concept performed in the human mind, including observation, evaluation, judgement or opinion (see MPEP 2106.04(a)(2) subsection 3). Here it is seen as evaluation.
determining the relational contribution degree of the causal relationship between the first factor and the third factor to the target observed data based on observed data of the first factor, the first change rate, and the second change rate
This limitation is directed towards the abstract idea of a mental process, or a concept performed in the human mind, including observation, evaluation, judgement or opinion (see MPEP 2106.04(a)(2) subsection 3). Here it is seen as evaluation.
In regards to Claim 31:
Step 2A Prong 1: Does the claim recite a law of nature, a natural phenomenon, or an abstract idea?
Yes, the claim does recite a(n) abstract idea.
Claim 31 recites the following abstract ideas:
wherein the causal relationship comprises a linear causal relationship
This limitation is directed towards the continuation of the abstract idea of a mental process, or a concept performed in the human mind, including observation, evaluation, judgement or opinion (see MPEP 2106.04(a)(2) subsection 3). Here it is seen as the continuation of the abstract ideas in claim 18 relating towards the use of the causal relationship.
In regards to Claim 32:
Step 1: Is the claim directed towards a process, machine, manufacture, or composition of matter?
Yes, it is directed towards a machine.
Step 2A Prong 1: Does the claim recite a law of nature, a natural phenomenon, or an abstract idea?
Yes, the claim does recite a(n) abstract idea.
Claim 32 recites the following abstract ideas:
determining a contribution degree of a first factor of the plurality of factors to target observed data of the target factor based on the causal structure and the observed data corresponding to the plurality of factors
This limitation is directed towards the abstract idea of a mental process, or a concept performed in the human mind, including observation, evaluation, judgement or opinion (see MPEP 2106.04(a)(2) subsection 3). Here it is seen as evaluation.
Step 2A Prong 2: Does the claim recite additional elements that integrate the exception into a practical application of the exception?
No, the application does not recite any additional elements that would integrate the abstract idea into a practical application.
Claim 32 recites the following additional elements:
An electronic device, comprising: at least one processing unit; and at least one memory coupled to the at least one processing unit and storing instructions executable by the at least one processing unit, the instructions, when executed by the at least one processing unit, causing the device to perform acts comprising
At a high level of generality, this is an activity of using a processor or other computer parts as an “apply it” use (see MPEP 2106.05(f)).
obtaining observed data corresponding to a plurality of factors to be analyzed
This limitation is directed towards the insignificant extra solution activity of mere data gathering (see MPEP § 2106.05(g)).
in response to one of the plurality of factors being selected as a target factor, obtaining a causal structure of the plurality of factors, the causal structure indicating causal relationships between the plurality of factors
This limitation is directed towards the insignificant extra solution activity of mere data gathering (see MPEP § 2106.05(g)).
and the target factor being any of customer satisfaction with telecom operators, a blood pressure of a patient, sales of a target commodity, and software development
This limitation is directed towards linking or indicating a field of use or technological environment (see MPEP 2106.05(h)).
and the target observed data comprising: based on the target factor being of the customer satisfaction with telecom operators, customer consumption behavior data comprising an age of a customer, a monthly consumption of an Internet traffic, a ratio of free traffic, and a total monthly consumption of a plurality of Internet traffics including the Internet traffic, based on the target factor being the blood pressure of the patient, heart rates, cardiac outputs, allergy indicators, total peripheral vascular resistance, catecholamine release, and blood pressure , based on the target factor being sales of the target commodity, commodity promotion investment, commodity display investment, sales staff investment, advertising investment, and new commodity marketing investment, and based on the target factor being software development, development cycle, resources invested in development, a software architecture method, a number of software architecture levels, a code length, a number of functions, a programming language, a number of modules, a failure rate of unit testing, a failure rate of block box testing, a failure rate of white box testing, and a failure rate of a running stage
This limitation is directed towards linking or indicating a field of use or technological environment (see MPEP 2106.05(h)).
Step 2B: Does the claim as a whole amount to significantly more than the judicial exception?
No, the claim as a whole does not amount to significantly more than the judicial exception. All elements of the claim, viewed individually or wholistically, do not provide an inventive concept or otherwise significantly more than the abstract idea itself.
Claim 32 recites the following additional elements:
An electronic device, comprising: at least one processing unit; and at least one memory coupled to the at least one processing unit and storing instructions executable by the at least one processing unit, the instructions, when executed by the at least one processing unit, causing the device to perform acts comprising
At a high level of generality, this is an activity of using a processor or other computer parts as an “apply it” use (see MPEP 2106.05(f)). At said high level of generality, a processor and other computer parts appears to be an implementation of the abstract idea on a computer, so merely using a computer as a tool to perform the abstract idea.
obtaining observed data corresponding to a plurality of factors to be analyzed
This limitation is directed towards the insignificant extra solution activity of mere data gathering (see MPEP § 2106.05(g)). This is a well understood, routine, conventional activity of transmitting data (see MPEP 2106.05(d) example i in computer functions).
in response to one of the plurality of factors being selected as a target factor, obtaining a causal structure of the plurality of factors, the causal structure indicating causal relationships between the plurality of factors
This limitation is directed towards the insignificant extra solution activity of mere data gathering (see MPEP § 2106.05(g)). This is a well understood, routine, conventional activity of transmitting data (see MPEP 2106.05(d) example i in computer functions).
and the target factor being any of customer satisfaction with telecom operators, a blood pressure of a patient, sales of a target commodity, and software development
This limitation is directed towards linking or indicating a field of use or technological environment (see MPEP 2106.05(h)). Limitations that amount to merely linking/indicating to a field of use or technological environment, such having the data be related to field like power/electricity (see MPEP 2106.05(h)(vi)), do not amount to significantly more than the exception itself.
and the target observed data comprising: based on the target factor being of the customer satisfaction with telecom operators, customer consumption behavior data comprising an age of a customer, a monthly consumption of an Internet traffic, a ratio of free traffic, and a total monthly consumption of a plurality of Internet traffics including the Internet traffic, based on the target factor being the blood pressure of the patient, heart rates, cardiac outputs, allergy indicators, total peripheral vascular resistance, catecholamine release, and blood pressure , based on the target factor being sales of the target commodity, commodity promotion investment, commodity display investment, sales staff investment, advertising investment, and new commodity marketing investment, and based on the target factor being software development, development cycle, resources invested in development, a software architecture method, a number of software architecture levels, a code length, a number of functions, a programming language, a number of modules, a failure rate of unit testing, a failure rate of block box testing, a failure rate of white box testing, and a failure rate of a running stage
This limitation is directed towards linking or indicating a field of use or technological environment (see MPEP 2106.05(h)). Limitations that amount to merely linking/indicating to a field of use or technological environment, such having the data be related to field like power/electricity (see MPEP 2106.05(h)(vi)), do not amount to significantly more than the exception itself.
In regards to Claim 33:
Step 2A Prong 2: Does the claim recite additional elements that integrate the exception into a practical application of the exception?
No, the application does not recite any additional elements that would integrate the abstract idea into a practical application.
Claim 33 recites the following additional elements:
receiving a first user input specifying the observed data corresponding to the plurality of factors
This limitation is directed towards the insignificant extra solution activity of mere data gathering (see MPEP § 2106.05(g)).
Step 2B: Does the claim as a whole amount to significantly more than the judicial exception?
No, the claim as a whole does not amount to significantly more than the judicial exception. All elements of the claim, viewed individually or wholistically, do not provide an inventive concept or otherwise significantly more than the abstract idea itself.
Claim 33 recites the following additional elements:
receiving a first user input specifying the observed data corresponding to the plurality of factors
This limitation is directed towards the insignificant extra solution activity of mere data gathering (see MPEP § 2106.05(g)). This is a well understood, routine, conventional activity of transmitting data (see MPEP 2106.05(d) example i in computer functions).
In regards to Claim 34:
Step 2A Prong 1: Does the claim recite a law of nature, a natural phenomenon, or an abstract idea?
Yes, the claim does recite a(n) abstract idea.
Claim 34 recites the following abstract ideas:
in accordance with a determination that the type of analysis is a type of average analysis, averaging the plurality of data items of each of the plurality of factors to determine observed data of the factor
This limitation is directed towards the abstract idea of a mental process, or a concept performed in the human mind, including observation, evaluation, judgement or opinion (see MPEP 2106.04(a)(2) subsection 3). Here it is seen as evaluation and judgement.
in accordance with a determination that the type of analysis is a type of summing analysis, aggregating the plurality of data items of each of the plurality of factors to determine observed data of the factor
This limitation is directed towards the abstract idea of a mental process, or a concept performed in the human mind, including observation, evaluation, judgement or opinion (see MPEP 2106.04(a)(2) subsection 3). Here it is seen as evaluation and judgement.
Step 2A Prong 2: Does the claim recite additional elements that integrate the exception into a practical application of the exception?
No, the application does not recite any additional elements that would integrate the abstract idea into a practical application.
Claim 34 recites the following additional elements:
receiving a second user input specifying a type of analysis and a plurality of data items of each of the plurality of factors within a plurality of time ranges
This limitation is directed towards the insignificant extra solution activity of mere data gathering (see MPEP § 2106.05(g)).
Step 2B: Does the claim as a whole amount to significantly more than the judicial exception?
No, the claim as a whole does not amount to significantly more than the judicial exception. All elements of the claim, viewed individually or wholistically, do not provide an inventive concept or otherwise significantly more than the abstract idea itself.
Claim 34 recites the following additional elements:
receiving a second user input specifying a type of analysis and a plurality of data items of each of the plurality of factors within a plurality of time ranges
This limitation is directed towards the insignificant extra solution activity of mere data gathering (see MPEP § 2106.05(g)). This is a well understood, routine, conventional activity of transmitting data (see MPEP 2106.05(d) example i in computer functions).
In regards to Claim 35:
Step 2A Prong 2: Does the claim recite additional elements that integrate the exception into a practical application of the exception?
No, the application does not recite any additional elements that would integrate the abstract idea into a practical application.
Claim 35 recites the following additional elements:
receiving a third user input specifying the target factor
This limitation is directed towards the insignificant extra solution activity of mere data gathering (see MPEP § 2106.05(g)).
Step 2B: Does the claim as a whole amount to significantly more than the judicial exception?
No, the claim as a whole does not amount to significantly more than the judicial exception. All elements of the claim, viewed individually or wholistically, do not provide an inventive concept or otherwise significantly more than the abstract idea itself.
Claim 35 recites the following additional elements:
receiving a third user input specifying the target factor
This limitation is directed towards the insignificant extra solution activity of mere data gathering (see MPEP § 2106.05(g)). This is a well understood, routine, conventional activity of transmitting data (see MPEP 2106.05(d) example i in computer functions).
In regards to Claim 36:
Step 2A Prong 1: Does the claim recite a law of nature, a natural phenomenon, or an abstract idea?
Yes, the claim does recite a(n) abstract idea.
Claim 36 recites the following abstract ideas:
determining at least one of a base contribution degree of the first factor to the target observed data independently of other factors among the plurality of factors, a total contribution degree of the first factor to the target observed data, the total contribution degree indicating a total sum of contribution degrees of the first factor to the target observed data and at least one second factor of the plurality of factors to the target observed data via the first factor, and a relational contribution degree of a causal relationship between the first factor and a third factor of the plurality of factors to the target observed data
This limitation is directed towards the abstract idea of a mental process, or a concept performed in the human mind, including observation, evaluation, judgement or opinion (see MPEP 2106.04(a)(2) subsection 3). Here it is seen as evaluation.
In regards to Claim 37:
Step 1: Is the claim directed towards a process, machine, manufacture, or composition of matter?
Yes, it is directed towards a manufacture.
Step 2A Prong 1: Does the claim recite a law of nature, a natural phenomenon, or an abstract idea?
Yes, the claim does recite a(n) abstract idea.
Claim 37 recites the following abstract ideas:
determining a contribution degree of a first factor of the plurality of factors to target observed data of the target factor based on the causal structure and the observed data corresponding to the plurality of factors
This limitation is directed towards the abstract idea of a mental process, or a concept performed in the human mind, including observation, evaluation, judgement or opinion (see MPEP 2106.04(a)(2) subsection 3). Here it is seen as evaluation.
Step 2A Prong 2: Does the claim recite additional elements that integrate the exception into a practical application of the exception?
No, the application does not recite any additional elements that would integrate the abstract idea into a practical application.
Claim 37 recites the following additional elements:
A computer-readable storage medium having computer-executable instructions stored thereon which are executed by a processor to perform acts comprising
At a high level of generality, this is an activity of using a processor or other computer parts as an “apply it” use (see MPEP 2106.05(f)).
obtaining observed data corresponding to a plurality of factors to be analyzed
This limitation is directed towards the insignificant extra solution activity of mere data gathering (see MPEP § 2106.05(g)).
in response to one of the plurality of factors being selected as a target factor, obtaining a causal structure of the plurality of factors, the causal structure indicating causal relationships between the plurality of factors
This limitation is directed towards the insignificant extra solution activity of mere data gathering (see MPEP § 2106.05(g)).
and the target factor being any of customer satisfaction with telecom operators, a blood pressure of a patient, sales of a target commodity, and software development
This limitation is directed towards linking or indicating a field of use or technological environment (see MPEP 2106.05(h)).
and the target observed data comprising: based on the target factor being of the customer satisfaction with telecom operators, customer consumption behavior data comprising an age of a customer, a monthly consumption of an Internet traffic, a ratio of free traffic, and a total monthly consumption of a plurality of Internet traffics including the Internet traffic, based on the target factor being the blood pressure of the patient, heart rates, cardiac outputs, allergy indicators, total peripheral vascular resistance, catecholamine release, and blood pressure , based on the target factor being sales of the target commodity, commodity promotion investment, commodity display investment, sales staff investment, advertising investment, and new commodity marketing investment, and based on the target factor being software development, development cycle, resources invested in development, a software architecture method, a number of software architecture levels, a code length, a number of functions, a programming language, a number of modules, a failure rate of unit testing, a failure rate of block box testing, a failure rate of white box testing, and a failure rate of a running stage
This limitation is directed towards linking or indicating a field of use or technological environment (see MPEP 2106.05(h)).
Step 2B: Does the claim as a whole amount to significantly more than the judicial exception?
No, the claim as a whole does not amount to significantly more than the judicial exception. All elements of the claim, viewed individually or wholistically, do not provide an inventive concept or otherwise significantly more than the abstract idea itself.
Claim 37 recites the following additional elements:
A computer-readable storage medium having computer-executable instructions stored thereon which are executed by a processor to perform acts comprising
At a high level of generality, this is an activity of using a processor or other computer parts as an “apply it” use (see MPEP 2106.05(f)). At said high level of generality, a processor and other computer parts appears to be an implementation of the abstract idea on a computer, so merely using a computer as a tool to perform the abstract idea.
obtaining observed data corresponding to a plurality of factors to be analyzed
This limitation is directed towards the insignificant extra solution activity of mere data gathering (see MPEP § 2106.05(g)). This is a well understood, routine, conventional activity of transmitting data (see MPEP 2106.05(d) example i in computer functions).
in response to one of the plurality of factors being selected as a target factor, obtaining a causal structure of the plurality of factors, the causal structure indicating causal relationships between the plurality of factors
This limitation is directed towards the insignificant extra solution activity of mere data gathering (see MPEP § 2106.05(g)). This is a well understood, routine, conventional activity of transmitting data (see MPEP 2106.05(d) example i in computer functions).
and the target factor being any of customer satisfaction with telecom operators, a blood pressure of a patient, sales of a target commodity, and software development
This limitation is directed towards linking or indicating a field of use or technological environment (see MPEP 2106.05(h)). Limitations that amount to merely linking/indicating to a field of use or technological environment, such having the data be related to field like power/electricity (see MPEP 2106.05(h)(vi)), do not amount to significantly more than the exception itself.
and the target observed data comprising: based on the target factor being of the customer satisfaction with telecom operators, customer consumption behavior data comprising an age of a customer, a monthly consumption of an Internet traffic, a ratio of free traffic, and a total monthly consumption of a plurality of Internet traffics including the Internet traffic, based on the target factor being the blood pressure of the patient, heart rates, cardiac outputs, allergy indicators, total peripheral vascular resistance, catecholamine release, and blood pressure , based on the target factor being sales of the target commodity, commodity promotion investment, commodity display investment, sales staff investment, advertising investment, and new commodity marketing investment, and based on the target factor being software development, development cycle, resources invested in development, a software architecture method, a number of software architecture levels, a code length, a number of functions, a programming language, a number of modules, a failure rate of unit testing, a failure rate of block box testing, a failure rate of white box testing, and a failure rate of a running stage
This limitation is directed towards linking or indicating a field of use or technological environment (see MPEP 2106.05(h)). Limitations that amount to merely linking/indicating to a field of use or technological environment, such having the data be related to field like power/electricity (see MPEP 2106.05(h)(vi)), do not amount to significantly more than the exception itself.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 18, 19, 21, 23, 31, 32, 33, 35, 37 is/are rejected under 35 U.S.C. 103 as being unpatentable over Mueller et al (US 20210256406 A1), referred to as Mueller in this document, and further in view of Abreu (US 20020049389 A1), referred to as Abreu in this document.
Regarding Claim 18:
Mueller teaches:
obtaining observed data corresponding to a plurality of factors to be analyzed
[Mueller Figure 1A]
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Mueller Figure 1A shows multiple methods of user input in a user interface, including the ability to upload a data file [obtaining observed data corresponding to a plurality of factors to be analyzed].
in response to one of the plurality of factors being selected as a target factor, obtaining a causal structure of the plurality of factors, the causal structure indicating causal relationships between the plurality of factors
[Mueller Figure 1B]
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Mueller figure 1B shows the ability to select a target (at the top of Figure 1B) [in response to one of the plurality of factors being selected as a target factor] as well as a causal graph [obtaining a causal structure of the plurality of factors, the causal structure indicating causal relationships between the plurality of factors] based on the input data given from Figure 1A.
Support for the idea of the causal structure is given by [Mueller 0062]: “The present disclosure relates to a system and method associated with expedient determination of causal models in observing time or static based phenomena. Even more particularly, the present invention relates to a novel system and method that implements a novel visual analytics framework for expedient visualization, modeling, and inference of causal model structures and causal sequences.”
and determining a contribution degree of a first factor of the plurality of factors to target observed data of the target factor based on the causal structure and the observed data corresponding to the plurality of factors
[Mueller 0194]: “One can further generalize this theory to a set of causes X of an effect e. The system would measure the influence of X towards e [and determining a contribution degree of a first factor of the plurality of factors to target observed data of the target factor based on the causal structure and the observed data corresponding to the plurality of factors] by calculating the change of the probability of e as P(e|X)−P(e) or the change of expected value of ve as E[ve|X]−E[ve], depending on the definition of e. Note that while the conditional probability is bounded within [0, 1], the expected value could be any amount, and either positive or negative.”
Mueller does not explicitly teach:
and the target factor being any of customer satisfaction with telecom operators, a blood pressure of a patient, sales of a target commodity, and software development
and the target observed data comprising: based on the target factor being of the customer satisfaction with telecom operators, customer consumption behavior data comprising an age of a customer, a monthly consumption of an Internet traffic, a ratio of free traffic, and a total monthly consumption of a plurality of Internet traffics including the Internet traffic, based on the target factor being the blood pressure of the patient, heart rates, cardiac outputs, allergy indicators, total peripheral vascular resistance, catecholamine release, and blood pressure , based on the target factor being sales of the target commodity, commodity promotion investment, commodity display investment, sales staff investment, advertising investment, and new commodity marketing investment, and based on the target factor being software development, development cycle, resources invested in development, a software architecture method, a number of software architecture levels, a code length, a number of functions, a programming language, a number of modules, a failure rate of unit testing, a failure rate of block box testing, a failure rate of white box testing, and a failure rate of a running stage
Mueller notes the application of multiple fields for the factors to be from such as medical with blood glucose/sugar [Mueller 0179], weather with wind pressure [Mueller 0237], and marketing [Mueller 0156]. Meaning Mueller teaches that varying fields of information are utilized in finding contribution of factors, but Mueller does not explicitly note the exact factors of the current application.
Abreu teaches:
and the target factor being any of customer satisfaction with telecom operators, a blood pressure of a patient, sales of a target commodity, and software development
[Abreu 0246]: "The same applies to a variety of disorders including heart attacks. Thus, if a patient has a family history of heart disease, has high cholesterol or high blood pressure [and the target factor being any of customer satisfaction with telecom operators, a blood pressure of a patient, sales of a target commodity, and software development where blood pressure of a patient is embodiment particularly noted in this reference], the patient uses the ICL for cardiac markers on a periodic basis in order to detect the presence of markers before a potentially fatal event, such as a heart attack, occurs."
and the target observed data comprising: based on the target factor being of the customer satisfaction with telecom operators, customer consumption behavior data comprising an age of a customer, a monthly consumption of an Internet traffic, a ratio of free traffic, and a total monthly consumption of a plurality of Internet traffics including the Internet traffic, based on the target factor being the blood pressure of the patient, heart rates, cardiac outputs, allergy indicators, total peripheral vascular resistance, catecholamine release, and blood pressure , based on the target factor being sales of the target commodity, commodity promotion investment, commodity display investment, sales staff investment, advertising investment, and new commodity marketing investment, and based on the target factor being software development, development cycle, resources invested in development, a software architecture method, a number of software architecture levels, a code length, a number of functions, a programming language, a number of modules, a failure rate of unit testing, a failure rate of block box testing, a failure rate of white box testing, and a failure rate of a running stage
[Abreu 0246]: "The same applies to a variety of disorders including heart attacks. Thus, if a patient has a family history of heart disease, has high cholesterol or high blood pressure [and the target observed data comprising:… based on the target factor being the blood pressure of the patient][and blood pressure], the patient uses the ICL for cardiac markers on a periodic basis in order to detect the presence of markers before a potentially fatal event, such as a heart attack, occurs."
[Abreu 0102]: "Several parameters can be detected with the invention including a complete non-invasive analysis of blood components, measurement of systemic and ocular blood flow, measurement of heart rate [heart rates] and respiratory rate, tracking operations, detection of ovulation, detection of radiation and drug effects, diagnosis of ocular and systemic disorders and the like. The invention also provides a new method and apparatus for somnolence awareness, activation of devices by disabled individuals, a new drug delivery system and new therapy for ocular and neurologic disorders, and treatment of cancer in the eye or other parts of the body, and an evaluation system for the overall health status of an individual."
[Abreu 1227]: "The body maintains ocular blood flow constant, whereas skin, muscle, and splanenic blood flow varies with changing cardiac output [cardiac outputs] and ambient conditions. Oxygen in the eye can continuously monitor perfusion and detect early hemodynamic changes."
[Abreu 1055]: "The ICL technology, by providing a continuous or quasi-continuous evaluation, can identify a mutant gene, for instance related to cancer or disease, among a large number of normal genes and be used for screening high risk populations or monitoring high risk patients undergoing treatment as well as identifying occult allergies [allergy indicators] and occult diseases and risk for certain diseases and reactions to drugs allowing preventive measures to be taken before injury or illness occur or timely treating the illness before significant damage occurs."
[Abreu 0896]: "The eye and the brain are hemodynamically linked by the carotid artery and the autonomic nervous system. Pathological changes in the carotid, brain, heart, and the sympathetic nervous system can secondarily affect the blood flow to the eye. The eye and the brain are low vascular resistance [total peripheral vascular resistance total peripheral vascular resistance is interpreted as a variant of vascular resistance and this reference teaches that vascular resistance is data that is utilized or known] systems with high reactivity. The arterial flow to the brain is provided by the carotid artery. The ophthalmic artery branches off of the carotid at a 90 degree angle and measures approximately 0.5 mm in diameter in comparison to the carotid which measures 5 mm in diameter. Thus, most processes that affect the flow to the brain will have a profound effect on the eye"
catecholamine release
[Abreu 0165]: "Moreover, the aqueous layer also holds critical metabolites such as glucose, urea, catecholamines [catecholamine release], and lactate, as well as gases such as oxygen and carbon dioxide. Furthermore, any exogenous substances found in the blood stream such as drugs, radioactive compounds and the like are present in the tear fluid. Any compound present in the blood can potentially noninvasively be evaluated with the apparatus of the invention with the data transmitted and processed at a remotely located station."
One of ordinary skill in the art, prior to the effective filing date would have been motivated to combine Mueller and Abreu. Mueller and Abreu are in the same field of endeavor of machine learning or data analysis ([Abreu 0296]: "The present invention reduces variability due to tissue structure, interfering constituents, and noise contribution to the signal of the substance of interest, ultimately substantially reducing the number of variables and the complexity of data analysis, either by empirical or physical methods. The empirical methods including Partial Least squares (PLS), principal component analysis, artificial neural networks, and the like while physical methods include chemometric techniques, mathematical models, and the like.") and/or medical ([Mueller 0179]). Mueller and Abreu would have been motivated to be combined in order to use medical related factors to detect markers or indicators of problems before bigger issues arise ([Abreu 0244]: "A surveillance system can be used in the civilian environment as for instance detecting the presence of tumor markers, cardiac markers, infectious agents and the like. Very frequently the body provides information in the form of markers before some serious illnesses occur but unfortunately those markers are not identified on a timely fashion. It is known that certain tumors release markers and chemicals before going out of control and creating generalized damage and spread. If patients could have access to those blood tests on a timely fashion, many cancers could be eliminated before causing irreversible and widespread damage."). When combining the motivation of medical information from Abreu with the known use of different fields of information from Mueller, as noted earlier, the combination of the factors shown in Abreu become apparent for use in a causal model like Mueller teaches.
Regarding Claim 19:
The method of claim 18 is taught by Mueller and Abreu.
Mueller teaches:
receiving a first user input specifying the observed data corresponding to the plurality of factors
[Mueller Figure 1A]
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Mueller Figure 1A shows multiple methods of user input in a user interface, including the ability to upload a data file [receiving a first user input specifying the observed data corresponding to the plurality of factors].
Further support for user input is given by [Mueller 0302]: “The computing system 100 may further include an alphanumeric input device 114, a user interface (UI) navigation device (e.g. mouse). In certain embodiments, a video display unit, input device and UI navigation device (and/or other control devices) may be incorporated into a touch screen display. The computing system 100 may include input device(s) 114 (e.g., a keyboard), cursor control device(s) 116 (e.g., a mouse), disk drive unit(s) 118, signal generation device(s) 119 (e.g., a speaker or remote control), and network interface device(s) 124.”
Regarding Claim 21:
The method of claim 18 is taught by Mueller and Abreu.
Mueller teaches:
receiving a third user input specifying the target factor
[Mueller Figure 1B] shows a target input [receiving a third user input specifying the target factor] at the top of the figure.
Regarding Claim 23:
The method of claim 18 is taught by Mueller and Abreu.
Mueller teaches:
presenting the contribution degree of the first factor to the target observed data to a user by at least one of: presenting the contribution degree in association with the causal structure, presenting the contribution degree in association with the target observed data, and separately presenting the contribution degree
[Mueller Figure 1]
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Mueller Figure 1 shows a user interface presenting numerous aspects of the causal graph, as well as the causal graph [presenting the contribution degree of the first factor to the target observed data to a user by at least one of: presenting the contribution degree in association with the causal structure, presenting the contribution degree in association with the target observed data, and separately presenting the contribution degree].
The idea of the contribution degree is taught particularly by Mueller in [Mueller 0194]: “One can further generalize this theory to a set of causes X of an effect e. The system would measure the influence of X towards e by calculating the change of the probability of e as P(e|X)−P(e) or the change of expected value of ve as E[ve|X]−E[ve], depending on the definition of e. Note that while the conditional probability is bounded within [0, 1], the expected value could be any amount, and either positive or negative.”
Further support for input and output devices is given by [Mueller 0302]: “The computing system 100 may further include an alphanumeric input device 114, a user interface (UI) navigation device (e.g. mouse). In certain embodiments, a video display unit, input device and UI navigation device (and/or other control devices) may be incorporated into a touch screen display. The computing system 100 may include input device(s) 114 (e.g., a keyboard), cursor control device(s) 116 (e.g., a mouse), disk drive unit(s) 118, signal generation device(s) 119 (e.g., a speaker or remote control), and network interface device(s) 124.”
Regarding Claim 31:
The method of claim 18 is taught by Mueller and Abreu.
Mueller teaches:
wherein the causal relationship comprises a linear causal relationship
[Mueller 0093]: “Several causal modeling methods can be used to parameterize the learned DAG (Directed Acyclic Graph). The two most common choices are Bayesian Networks (BN) and Structural Causal Models (SCM). The former quantifies causal relations with conditional probability tables, and the latter quantifies causal relations with linear functions [wherein the causal relationship comprises a linear causal relationship] plus Gaussian noise, e.g. linear regression and logistic regressions.”
Regarding Claim 32:
Mueller teaches:
An electronic device, comprising: at least one processing unit; and at least one memory coupled to the at least one processing unit and storing instructions executable by the at least one processing unit, the instructions, when executed by the at least one processing unit, causing the device to perform acts comprising
[Mueller 0017]: “In accordance with an embodiment or aspect, the present technology is directed to a system and method associated with generating an interactive visualization of causal models used in analytics of data. The system and method comprises a memory configured to store instructions [and at least one memory coupled to the at least one processing unit and storing instructions executable by the at least one processing unit, the instructions, when executed by the at least one processing unit, causing the device to perform acts comprising]; and a visual analytics processing device coupled to the memory. The processing device [An electronic device, comprising: at least one processing unit;] executes a data visualization application with the instructions stored in memory, wherein the data visualization application is configured to perform various operations.”
This rest of this claim is analogous to claim 18.
Regarding Claim 33:
The device of claim 32 is taught by Mueller and Abreu.
This claim is analogous to claim 19.
Regarding Claim 35:
The device of claim 32 is taught by Mueller and Abreu.
This claim is analogous to claim 21.
Regarding Claim 37:
Mueller teaches:
[Mueller 0308]: “The term “machine-readable medium” [A computer-readable storage medium having computer-executable instructions stored thereon which are executed by a processor to perform acts comprising] shall accordingly be taken to include, but not be limited to: solid-state memories such as a memory card or other package that houses one or more read-only (non-volatile) memories, random access memories, or other re-writable (volatile) memories; magneto-optical or optical medium such as a disk or tape; and/or a digital file attachment to e-mail or other self-contained information archive or set of archives is considered a distribution medium equivalent to a tangible storage medium.”
The rest of this claim is analogous to claim 18.
Claims 20, 34 is/are rejected under 35 U.S.C. 103 as being unpatentable over Mueller et al (US 20210256406 A1), referred to as Mueller in this document, and further in view of Abreu (US 20020049389 A1), referred to as Abreu in this document, and further in view of Pearl (“An Introduction to Causal Inference”), referred to as Pearl in this document.
Regarding Claim 20:
The method of claim 18 is taught by Mueller and Abreu.
Mueller teaches:
receiving a second user input specifying a type of analysis and a plurality of data items of each of the plurality of factors
[Mueller Figure 1A]
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Mueller Figure 1A shows multiple options for user input on top of the input data including what variables should be looked at, as well as thresholds or data scaling methods [receiving a second user input specifying a type of analysis and a plurality of data items of each of the plurality of factors].
Further support for user input is given by [Mueller 0302]: “The computing system 100 may further include an alphanumeric input device 114, a user interface (UI) navigation device (e.g. mouse). In certain embodiments, a video display unit, input device and UI navigation device (and/or other control devices) may be incorporated into a touch screen display. The computing system 100 may include input device(s) 114 (e.g., a keyboard), cursor control device(s) 116 (e.g., a mouse), disk drive unit(s) 118, signal generation device(s) 119 (e.g., a speaker or remote control), and network interface device(s) 124.”
within a plurality of time ranges
[Mueller 0018]: “In accordance with an embodiment or aspect, disclosed is a system and method that includes the processing device perform the various operations that include receiving time series data [within a plurality of time ranges] in the analytics of time-based phenomena associated with a data set.”
and in accordance with a determination that the type of analysis is a type of average analysis, averaging the plurality of data items of each of the plurality of factors to determine observed data of the factor
[Mueller 0197]: “In order to identify the real causes that can better explain the effect, Eells (citing E. Eells. Probabilistic causality. Cambridge University Press, 1991) proposed the average significance of a potential cause c [and in accordance with a determination that the type of analysis is a type of average analysis, averaging the plurality of data items of each of the plurality of factors to determine observed data of the factor], among all potential causes X towards the effect e as defined by Equation (11) as…”
Mueller does not explicitly teach:
and in accordance with a determination that the type of analysis is a type of summing analysis, aggregating the plurality of data items of each of the plurality of factors to determine observed data of the factor
Pearl teaches:
and in accordance with a determination that the type of analysis is a type of summing analysis, aggregating the plurality of data items of each of the plurality of factors to determine observed data of the factor
[Pearl 6.1.1 Direct versus total effects page 40]: “The causal effect we have analyzed so far, P(y|do(x)), measures the total effect of a variable (or a set of variables) X on a response variable Y.”
[Pearl 6.1.4 Natural indirect effects page 45]: “In linear systems, where reversal of transitions amounts to negating the signs of their effects, we have the standard additive formula
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” [and in accordance with a determination that the type of analysis is a type of summing analysis, aggregating the plurality of data items of each of the plurality of factors to determine observed data of the factor]
Observed data is interpreted in light of the spec ([Current Application 0025]: “In the embodiments of the present disclosure, the term "causal structure" generally refers to a structure for describing causal relationships between multiple factors in a system. The term "factor" is also referred to as "variable." The term "observed data" refers to data which can be directly observed for a factor (variable). In some examples, observed data may be in the form of a value, and thus may also be referred to as "observed value."”).
One of ordinary skill in the art, prior to the effective filing date, would have been motivated to combine Mueller and Pearl. Mueller and Pearl are in the same field of endeavor of causal analysis or causal graphs. One of ordinary skill would have been motivated to combine Mueller and Pearl in order to incorporate ideas taught in Pearl, such as the summation of data items, as the information gathered through parts of causal analysis are useful for multiple fields to understand and help prove cause. Especially since such information can prevent costly effects ([Pearl 6.1.1 Direct versus total effects page 40-41]: “From a policy making viewpoint, an investigator may be interested in decomposing effects to quantify the extent to which racial salary disparity is due to educational disparity, or, taking a health-care example, the extent to which sensitivity to a given exposure can be reduced by eliminating sensitivity to an intermediate factor, standing between exposure and outcome. Another example concerns the identification of neural pathways in the brain or the structural features of protein signaling networks in molecular biology (Brent and Lok, 2005). Here, the decomposition of effects into their direct and indirect components carries theoretical scientific importance, for it tells us “how nature works” and, therefore, enables us to predict behavior under a rich variety of conditions.”).
Regarding Claim 34:
The device of claim 32 is taught by Mueller and Abreu.
This claim is analogous to claim 20.
Claims 22, 24-30, 36 is/are rejected under 35 U.S.C. 103 as being unpatentable over Mueller et al (US 20210256406 A1), referred to as Mueller in this document, and further in view of Abreu (US 20020049389 A1), referred to as Abreu in this document, and further in view of Pearl (“An Introduction to Causal Inference”), referred to as Pearl in this document, and further in view of Isozaki (US 20210124740 A1), referred to as Isozaki in this document.
Regarding Claim 22:
The method of claim 18 is taught by Mueller and Abreu.
Mueller teaches:
and a relational contribution degree of a causal relationship between the first factor and a third factor of the plurality of factors to the target observed data
[Mueller 0126]: “Besides the directional structure, parameterized relations also come with a set of statistical coefficients quantitatively measuring their respective strengths and significances. In an embodiment, the disclosed system and method comprises a visual interface in which the width of a path signifies the strength of the relation [and a relational contribution degree of a causal relationship between the first factor and a third factor of the plurality of factors to the target observed data] measured by linear (targeting numeric variables) or logistic (targeting categorical variables) regression coefficients. Using the color code for causal semantics, for example green paths 30 denote positive causal influence and red paths 31 denote a negative influence. Compound relations between levels of categorical variables and other variables are colored yellow 35. Node colors indicate variable type—blue for numeric and yellow for categorical. A node's border thickness suggests the level of fit of the variable's regression model measured by r-squared (for linear regression) or McFadden's pseudo r-squared (for logistic regression) coefficients, both have a value range of 0 to 1, in accordance with an embodiment.”
An alternative teaching is given by Isozaki:
and a relational contribution degree of a causal relationship between the first factor and a third factor of the plurality of factors to the target observed data
[Isozaki Figure 2]
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Isozaki figure 2 shows a value indicating the relation between factors [and a relational contribution degree of a causal relationship between the first factor and a third factor of the plurality of factors to the target observed data] on the edges of the diagram.
One of ordinary skill in the art, prior to the effective filing date, would have been motivated to combine Mueller and Isozaki. Mueller and Isozaki are in the same field of endeavor of causal analysis or causal graphs. One of ordinary skill in the art would have been motivated to combine Mueller and Isozaki in order to improve readability of graphs to users ([Isozaki 0031]: “One of the basic items in the analysis of multiple-variable data is to first examine the relation (correlation or cause-effect relation) between two variables. The relation between two variables can be expressed by a graph including nodes indicating variables and links connecting related variables. In such a graph, information indicating a relation such as correlation coefficients can be displayed in correlation with the links. By such a graph, it is possible to improve the readability of the relation between two variables, in particular.”).
Mueller does not explicitly teach:
determining at least one of a base contribution degree of the first factor to the target observed data independently of other factors among the plurality of factors
a total contribution degree of the first factor to the target observed data, the total contribution degree indicating a total sum of contribution degrees of the first factor to the target observed data and at least one second factor of the plurality of factors to the target observed data via the first factor
Pearl teaches:
determining at least one of a base contribution degree of the first factor to the target observed data independently of other factors among the plurality of factors
[Pearl 6.1.1 Direct versus total effects page 40]: “The term “direct effect” is meant to quantify an effect that is not mediated by other variables in the model or, more accurately, the sensitivity of Y to changes in X while all other factors in the analysis are held fixed [determining at least one of a base contribution degree of the first factor to the target observed data independently of other factors among the plurality of factors]. Naturally, holding those factors fixed would sever all causal paths from X to Y with the exception of the direct link X -> Y, which is not intercepted by any intermediaries.”
a total contribution degree of the first factor to the target observed data, the total contribution degree indicating a total sum of contribution degrees of the first factor to the target observed data and at least one second factor of the plurality of factors to the target observed data via the first factor
[Pearl 6.1.1 Direct versus total effects page 40]: “The causal effect we have analyzed so far, P(y|do(x)), measures the total effect of a variable (or a set of variables) X on a response variable Y. [a total contribution degree of the first factor to the target observed data, the total contribution degree indicating a total sum of contribution degrees of the first factor to the target observed data and at least one second factor of the plurality of factors to the target observed data via the first factor]”
[Pearl 6.1.4 Natural indirect effects page 45]: “In linear systems, where reversal of transitions amounts to negating the signs of their effects, we have the standard additive formula
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”
The motivation to use Pearl is the same as the motivation used for Pearl in claim 20.
Regarding Claim 24:
The method of claim 22 is taught by Mueller, Abreu, Isozaki, and Pearl.
Mueller teaches:
in accordance with a determination that the first factor is not the target factor, determining a change rate of the target factor with respect to the first factor based on a causal relationship between the first factor and the target factor as indicated by the causal structure
[Mueller 0126]: “Besides the directional structure, parameterized relations also come with a set of statistical coefficients quantitatively measuring their respective strengths and significances. In an embodiment, the disclosed system and method comprises a visual interface in which the width of a path signifies the strength of the relation [in accordance with a determination that the first factor is not the target factor, determining a change rate of the target factor with respect to the first factor based on a causal relationship between the first factor and the target factor as indicated by the causal structure] measured by linear (targeting numeric variables) or logistic (targeting categorical variables) regression coefficients. Using the color code for causal semantics, for example green paths 30 denote positive causal influence and red paths 31 denote a negative influence. Compound relations between levels of categorical variables and other variables are colored yellow 35. Node colors indicate variable type—blue for numeric and yellow for categorical. A node's border thickness suggests the level of fit of the variable's regression model measured by r-squared (for linear regression) or McFadden's pseudo r-squared (for logistic regression) coefficients, both have a value range of 0 to 1, in accordance with an embodiment.”
Mueller does not explicitly teach:
determining base data of the first factor based on the observed data of the plurality of factors and the causal structure, the base data of the first factor indicating a portion of the observed data of the first factor that is not affected by other factors among the plurality of factors
and determining the base contribution degree of the first factor to the target observed data based on the base data of the first factor and the change rate of the target factor with respect to the first factor
and in accordance with a determination that the first factor is the target factor, determining the base data of the first factor as the base contribution degree of the first factor to the target observed data
Pearl teaches:
determining base data of the first factor based on the observed data of the plurality of factors and the causal structure, the base data of the first factor indicating a portion of the observed data of the first factor that is not affected by other factors among the plurality of factors
and determining the base contribution degree of the first factor to the target observed data based on the base data of the first factor and the change rate of the target factor with respect to the first factor
and in accordance with a determination that the first factor is the target factor, determining the base data of the first factor as the base contribution degree of the first factor to the target observed data
[Pearl 6.1.1 Direct versus total effects page 40]: “The term “direct effect” is meant to quantify an effect [determining base data of the first factor based on the observed data of the plurality of factors and the causal structure, the base data of the first factor indicating a portion of the observed data of the first factor that is not affected by other factors among the plurality of factors] that is not mediated by other variables in the model or, more accurately, the sensitivity of Y to changes in X while all other factors in the analysis are held fixed [and determining the base contribution degree of the first factor to the target observed data based on the base data of the first factor and the change rate of the target factor with respect to the first factor][and in accordance with a determination that the first factor is the target factor, determining the base data of the first factor as the base contribution degree of the first factor to the target observed data as determining the base contribution for each factor will include performing the calculation on the target factor]. Naturally, holding those factors fixed would sever all causal paths from X to Y with the exception of the direct link X -> Y, which is not intercepted by any intermediaries.”
Regarding Claim 25:
The method of claim 24 is taught by Mueller, Abreu, Isozaki, and Pearl.
Mueller teaches:
wherein the causal structure is indicated by a causal graph comprising a plurality of nodes that represent the plurality of factors and edges that connect the plurality of nodes, and an edge directly connecting a pair of nodes among the plurality of nodes represents a direct causal relationship between a pair of factors corresponding to the pair of nodes, and wherein determining the change rate of the target factor with respect to the first factor comprises
[Mueller Figure 1B]
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Mueller Figure 1B shows a causal graph with nodes, edges, and nodes that are directly connected. [wherein the causal structure is indicated by a causal graph comprising a plurality of nodes that represent the plurality of factors and edges that connect the plurality of nodes, and an edge directly connecting a pair of nodes among the plurality of nodes represents a direct causal relationship between a pair of factors corresponding to the pair of nodes, and wherein determining the change rate of the target factor with respect to the first factor comprises]
determining, from the causal graph, at least one path from the first factor to the target factor, each of the at least one path comprising at least one edge in the causal graph; for each of the at least one path, determining a partial change rate of the target factor with respect to the first factor on the path based on a direct change rate of an effect factor with respect to a cause factor in a direct causal relationship represented by at least one edge included in the path; and determining a change rate of the target factor with respect to the first factor based on a sum of at least one partial change rate determined for the at least one path
[Mueller 0126]: “Besides the directional structure, parameterized relations also come with a set of statistical coefficients quantitatively measuring their respective strengths and significances. In an embodiment, the disclosed system and method comprises a visual interface in which the width of a path signifies the strength of the relation [determining, from the causal graph, at least one path from the first factor to the target factor, each of the at least one path comprising at least one edge in the causal graph; for each of the at least one path, determining a partial change rate of the target factor with respect to the first factor on the path based on a direct change rate of an effect factor with respect to a cause factor in a direct causal relationship represented by at least one edge included in the path; and determining a change rate of the target factor with respect to the first factor based on a sum of at least one partial change rate determined for the at least one path] measured by linear (targeting numeric variables) or logistic (targeting categorical variables) regression coefficients. Using the color code for causal semantics, for example green paths 30 denote positive causal influence and red paths 31 denote a negative influence. Compound relations between levels of categorical variables and other variables are colored yellow 35. Node colors indicate variable type—blue for numeric and yellow for categorical. A node's border thickness suggests the level of fit of the variable's regression model measured by r-squared (for linear regression) or McFadden's pseudo r-squared (for logistic regression) coefficients, both have a value range of 0 to 1, in accordance with an embodiment.”
The change rate presented in Mueller is seen as teaching partial change rate, as the change rate given fits the description of “the sum of at least one partial change rate determined for the at least one path”.
Regarding Claim 26:
The method of claim 24 is taught by Mueller, Abreu, Isozaki, and Pearl.
Mueller teaches:
in accordance with a determination that the causal structure indicates that the plurality of factors comprise at least one factor as a direct cause of the first cause, determining, from a direct causal relationship between the at least one factor and the first factor as indicated by the causal structure
[Mueller Figure 1B] shows edges that directly connect two nodes [in accordance with a determination that the causal structure indicates that the plurality of factors comprise at least one factor as a direct cause of the first cause, determining, from a direct causal relationship between the at least one factor and the first factor as indicated by the causal structure] in the causal structure.
at least one direct change rate of the first factor with respect to the at least one factor
[Mueller 0126]: “Besides the directional structure, parameterized relations also come with a set of statistical coefficients quantitatively measuring their respective strengths and significances. In an embodiment, the disclosed system and method comprises a visual interface in which the width of a path signifies the strength of the relation [at least one direct change rate of the first factor with respect to the at least one factor] measured by linear (targeting numeric variables) or logistic (targeting categorical variables) regression coefficients. Using the color code for causal semantics, for example green paths 30 denote positive causal influence and red paths 31 denote a negative influence. Compound relations between levels of categorical variables and other variables are colored yellow 35. Node colors indicate variable type—blue for numeric and yellow for categorical. A node's border thickness suggests the level of fit of the variable's regression model measured by r-squared (for linear regression) or McFadden's pseudo r-squared (for logistic regression) coefficients, both have a value range of 0 to 1, in accordance with an embodiment.”
Pearl teaches:
and determining base data of the first factor based on observed data of the first factor and the at least one factor and the at least one determined direct change rate
and in accordance with a determination that the causal structure indicates that the plurality of factors comprise no factor as a direct cause of the first factor, determining observed data of the first factor as base data of the first factor
[Pearl 6.1.1 Direct versus total effects page 40]: “The term “direct effect” is meant to quantify an effect that is not mediated by other variables in the model or, more accurately, the sensitivity of Y to changes in X while all other factors in the analysis are held fixed [and determining base data of the first factor based on observed data of the first factor and the at least one factor and the at least one determined direct change rate] [and in accordance with a determination that the causal structure indicates that the plurality of factors comprise no factor as a direct cause of the first factor, determining observed data of the first factor as base data of the first factor as determining the base contribution for each factor will include performing the calculation on a factor with no direct causes]. Naturally, holding those factors fixed would sever all causal paths from X to Y with the exception of the direct link X -> Y, which is not intercepted by any intermediaries.”
Motivation to combine with Pearl is the same as the motivation to combine with Pearl in claim 20.
Regarding Claim 27:
The method of claim 22 is taught by Mueller, Abreu, Isozaki, and Pearl.
Mueller teaches:
wherein the causal structure indicates that the at least one second factor is a direct cause of the first factor
[Mueller Figure 1B] shows nodes being directly connected to other nodes [wherein the causal structure indicates that the at least one second factor is a direct cause of the first factor].
determining at least one relational contribution degree of a direct causal relationship between the at least one second factor and the first factor to the target observed data
[Mueller 0126]: “Besides the directional structure, parameterized relations also come with a set of statistical coefficients quantitatively measuring their respective strengths and significances. In an embodiment, the disclosed system and method comprises a visual interface in which the width of a path signifies the strength of the relation [determining at least one relational contribution degree of a direct causal relationship between the at least one second factor and the first factor to the target observed data] measured by linear (targeting numeric variables) or logistic (targeting categorical variables) regression coefficients. Using the color code for causal semantics, for example green paths 30 denote positive causal influence and red paths 31 denote a negative influence. Compound relations between levels of categorical variables and other variables are colored yellow 35. Node colors indicate variable type—blue for numeric and yellow for categorical. A node's border thickness suggests the level of fit of the variable's regression model measured by r-squared (for linear regression) or McFadden's pseudo r-squared (for logistic regression) coefficients, both have a value range of 0 to 1, in accordance with an embodiment.”
An alternative teaching is given by Isozaki:
determining at least one relational contribution degree of a direct causal relationship between the at least one second factor and the first factor to the target observed data
[Isozaki Figure 2]
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Isozaki figure 2 shows a value indicating the relation between factors [determining at least one relational contribution degree of a direct causal relationship between the at least one second factor and the first factor to the target observed data] on the edges of the diagram.
The motivation to combine with Isozaki is the same as the motivation to combine in claim 22.
Pearl teaches:
determining a base contribution degree of the first factor to the target observed data
[Pearl 6.1.1 Direct versus total effects page 40]: “The term “direct effect” is meant to quantify an effect that is not mediated by other variables in the model or, more accurately, the sensitivity of Y to changes in X while all other factors in the analysis are held fixed [determining a base contribution degree of the first factor to the target observed data]. Naturally, holding those factors fixed would sever all causal paths from X to Y with the exception of the direct link X -> Y, which is not intercepted by any intermediaries.”
and determining the total contribution degree of the first factor to the target observed data comprises: … and determining the total contribution degree of the first factor to the target observed data based on a sum of the base contribution degree of the first factor to the target observed data and the at least one relational contribution degree
[Pearl 6.1.1 Direct versus total effects page 40]: “The causal effect we have analyzed so far, P(y|do(x)), measures the total effect of a variable (or a set of variables) X on a response variable Y. [and determining the total contribution degree of the first factor to the target observed data comprises: … and determining the total contribution degree of the first factor to the target observed data based on a sum of the base contribution degree of the first factor to the target observed data and the at least one relational contribution degree]”
[Pearl 6.1.4 Natural indirect effects page 45]: “In linear systems, where reversal of transitions amounts to negating the signs of their effects, we have the standard additive formula
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The motivation to combine with Pearl is the same motivation to combine with Pearl regarding claim 20.
Regarding Claim 28:
The method of claim 22 is taught by Mueller, Abreu, Isozaki, and Pearl.
Mueller teaches:
wherein the causal structure indicates that the first factor is a cause of the third factor
[Mueller Figure 1B] shows nodes in a causal structure that influence or cause other factors [wherein the causal structure indicates that the first factor is a cause of the third factor].
determining a change rate of the target factor with respect to the third factor based on a causal relationship between the third factor and the target factor as indicated by the causal structure
and determining the relational contribution degree of the causal relationship between the first factor and the third factor to the target observed data comprises
[Mueller 0126]: “Besides the directional structure, parameterized relations also come with a set of statistical coefficients quantitatively measuring their respective strengths and significances. In an embodiment, the disclosed system and method comprises a visual interface in which the width of a path signifies the strength of the relation [determining a change rate of the target factor with respect to the third factor based on a causal relationship between the third factor and the target factor as indicated by the causal structure][and determining the relational contribution degree of the causal relationship between the first factor and the third factor to the target observed data comprises] measured by linear (targeting numeric variables) or logistic (targeting categorical variables) regression coefficients. Using the color code for causal semantics, for example green paths 30 denote positive causal influence and red paths 31 denote a negative influence. Compound relations between levels of categorical variables and other variables are colored yellow 35. Node colors indicate variable type—blue for numeric and yellow for categorical. A node's border thickness suggests the level of fit of the variable's regression model measured by r-squared (for linear regression) or McFadden's pseudo r-squared (for logistic regression) coefficients, both have a value range of 0 to 1, in accordance with an embodiment.”
An alternative teaching is given by Isozaki:
and determining the relational contribution degree of the causal relationship between the first factor and the third factor to the target observed data comprises
[Isozaki Figure 2] shows a value indicating the relation between factors [and determining the relational contribution degree of the causal relationship between the first factor and the third factor to the target observed data comprises] on the edges of the diagram.
The motivation to combine with Isozaki is the same motivation to combine with Isozaki in claim 22.
Pearl teaches:
determining a base contribution degree
[Pearl 6.1.1 Direct versus total effects page 40]: “The term “direct effect” is meant to quantify an effect that is not mediated by other variables in the model or, more accurately, the sensitivity of Y to changes in X while all other factors in the analysis are held fixed [determining a base contribution degree]. Naturally, holding those factors fixed would sever all causal paths from X to Y with the exception of the direct link X -> Y, which is not intercepted by any intermediaries.”
and a total contribution degree of the third factor to the target observed data
[Pearl 6.1.1 Direct versus total effects page 40]: “The causal effect we have analyzed so far, P(y|do(x)), measures the total effect of a variable (or a set of variables) X on a response variable Y. [and a total contribution degree of the third factor to the target observed data]”
[Pearl 6.1.4 Natural indirect effects page 45]: “In linear systems, where reversal of transitions amounts to negating the signs of their effects, we have the standard additive formula
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and in accordance with a determination that the causal structure indicates that the first factor is an only cause of the third factor, determining a difference between the total contribution degree and the base contribution degree of the third factor as the relational contribution degree of the causal relationship between the first factor and the third factor to the target observed data
Pearl in combination with Mueller is seen as teaching [and in accordance with a determination that the causal structure indicates that the first factor is an only cause of the third factor, determining a difference between the total contribution degree and the base contribution degree of the third factor as the relational contribution degree of the causal relationship between the first factor and the third factor to the target observed data] as the teaching of total contribution and base contribution by Pearl make it known that the total contribution, called total effect by Pearl, is a combination of the effects from other factors. This means that remove parts from the total would leave the elements not removed. Thus removing the base contribution leaves only the other effects which would be the relational contribution given the circumstance noted in the claim limitations.
The same premise can be noted in the alternative combination with Isozaki, as Isozaki also teaches relational contribution and some other relevant parts including paragraphs 61 to 68, which note the idea of subtracting elements from a combination of explanatory variables to extract a relation.
[Isozaki 0061-0064]: “The coupling effect evaluation section 134 has a function of evaluating the relation between the target variable and the combinations of explanatory variables extracted by the relation variable group extraction section 133. First, the coupling effect evaluation section 134 calculates first information indicating the strength of the relation between the target variable and the combinations of explanatory variables extracted by the relation variable group extraction section 133. The first information is a value indicating the strength of the relation calculated based on entropy, the amount of mutual information, a correlation coefficient, a partial correlation coefficient, a p value of a test, other statistical measures of independence or conditional independence, or a combination thereof. The coupling effect is quantified by such a value. When this value is large, it means that the coupling effect is large, and when this value is small, it means that the coupling effect is small. The first information is also referred to as a first index of the coupling effect below. A first index J of the coupling effect in the case of three variables can be calculated as expressed by the following Equation:
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The motivation to use Pearl is the same as the motivation used for Pearl in claim 20.
Regarding Claim 29:
The method of claim 28 is taught by Mueller, Abreu, Isozaki, and Pearl.
Mueller teaches:
in accordance with a determination that the causal structure indicates that at least one fourth factor is a further cause of the third factor
[Mueller Figure 1B] shows a causal structure with nodes that effect nodes that then effect other nodes [in accordance with a determination that the causal structure indicates that at least one fourth factor is a further cause of the third factor] such as “SurfWind_V” to “PhotActiRadi” to “MixdLayrDpth”.
determining, based on the causal structure, a further relational contribution degree of a causal relationship between the at least one fourth factor and the third factor to the target observed data
[Mueller 0126]: “Besides the directional structure, parameterized relations also come with a set of statistical coefficients quantitatively measuring their respective strengths and significances. In an embodiment, the disclosed system and method comprises a visual interface in which the width of a path signifies the strength of the relation [determining, based on the causal structure, a further relational contribution degree of a causal relationship between the at least one fourth factor and the third factor to the target observed data] measured by linear (targeting numeric variables) or logistic (targeting categorical variables) regression coefficients. Using the color code for causal semantics, for example green paths 30 denote positive causal influence and red paths 31 denote a negative influence. Compound relations between levels of categorical variables and other variables are colored yellow 35. Node colors indicate variable type—blue for numeric and yellow for categorical. A node's border thickness suggests the level of fit of the variable's regression model measured by r-squared (for linear regression) or McFadden's pseudo r-squared (for logistic regression) coefficients, both have a value range of 0 to 1, in accordance with an embodiment.”
An alternative teaching is given by Isozaki:
determining, based on the causal structure, a further relational contribution degree of a causal relationship between the at least one fourth factor and the third factor to the target observed data
[Isozaki Figure 2] shows a value indicating the relation between factors [determining, based on the causal structure, a further relational contribution degree of a causal relationship between the at least one fourth factor and the third factor to the target observed data] on the edges of the diagram.
The motivation to combine with Isozaki is the same motivation to combine with Isozaki in claim 22.
Pearl teaches:
and determining the relational contribution degree of the causal relationship between the first factor and the third factor to the target observed data by subtracting a sum of the further relational contribution degree and the base contribution degree of the third factor to the target observed data from the total contribution degree of the third factor to the target observed data
Pearl is noted as teaching total contribution and base contribution in previous claims, such as claim 22.
Pearl in combination with Mueller is seen as teaching [and determining the relational contribution degree of the causal relationship between the first factor and the third factor to the target observed data by subtracting a sum of the further relational contribution degree and the base contribution degree of the third factor to the target observed data from the total contribution degree of the third factor to the target observed data] as the teaching of total contribution and base contribution by Pearl make it known that the total contribution, called total effect by Pearl, is a combination of the effects from other factors. This means that remove parts from the total would leave the elements not removed. Thus removing the base contribution leaves only the other effects which would be the wanted relational contribution given the circumstance noted in the claim limitations.
The same premise can be noted in the alternative combination with Isozaki, as Isozaki also teaches relational contribution and some other relevant parts including paragraphs 61 to 68, which note the idea of subtracting elements from a combination of explanatory variables to extract a relation. Further details are listed regarding claim 28.
The motivation to use Pearl is the same as the motivation used for Pearl in claim 20.
Regarding Claim 30:
The method of claim 22 is taught by Mueller, Abreu, Isozaki, and Pearl.
Mueller teaches:
wherein the causal structure indicates that the first factor is a cause of the third factor
[Mueller Figure 1B] shows a causal structure where notes influence other nodes [wherein the causal structure indicates that the first factor is a cause of the third factor].
and determining the relational contribution degree of the causal relationship between the first factor and the third factor to the target observed data comprises: determining a first change rate of the third factor with respect to the first factor from a causal relationship between the first factor and the third factor as indicated by the causal structure
determining a second change rate of the target factor with respect to the third factor from a causal relationship between the third factor and the target factor as indicated by the causal structure
[Mueller 0126]: “Besides the directional structure, parameterized relations also come with a set of statistical coefficients quantitatively measuring their respective strengths and significances. In an embodiment, the disclosed system and method comprises a visual interface in which the width of a path signifies the strength of the relation [and determining the relational contribution degree of the causal relationship between the first factor and the third factor to the target observed data comprises: determining a first change rate of the third factor with respect to the first factor from a causal relationship between the first factor and the third factor as indicated by the causal structure][determining a second change rate of the target factor with respect to the third factor from a causal relationship between the third factor and the target factor as indicated by the causal structure] measured by linear (targeting numeric variables) or logistic (targeting categorical variables) regression coefficients. Using the color code for causal semantics, for example green paths 30 denote positive causal influence and red paths 31 denote a negative influence. Compound relations between levels of categorical variables and other variables are colored yellow 35. Node colors indicate variable type—blue for numeric and yellow for categorical. A node's border thickness suggests the level of fit of the variable's regression model measured by r-squared (for linear regression) or McFadden's pseudo r-squared (for logistic regression) coefficients, both have a value range of 0 to 1, in accordance with an embodiment.”
Pearl teaches:
and determining the relational contribution degree of the causal relationship between the first factor and the third factor to the target observed data based on observed data of the first factor, the first change rate, and the second change rate
Pearl is noted as teaching total contribution and base contribution in previous claims, such as claim 22.
Pearl in combination with Mueller is seen as teaching [and determining the relational contribution degree of the causal relationship between the first factor and the third factor to the target observed data based on observed data of the first factor, the first change rate, and the second change rate] as the teaching of total contribution and base contribution by Pearl make it known that the total contribution, called total effect by Pearl, is a combination of the effects from other factors. This means that remove parts from the total would leave the elements not removed. Thus manipulating the effects within the total effects can be used to find the other effects which would be the wanted contribution given the circumstance noted in the claim limitations.
The motivation to use Pearl is the same as the motivation used for Pearl in claim 20.
Regarding Claim 36:
The device of claim 32 is taught by Mueller and Abreu.
This claim is analogous to claim 22.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Hasegawa Takashi (JP 201456448A) is considered relevant art, as the reference notes the calculation of forms of relevance or causal contributions between data. Some important examples are correlation coefficient (appears to be equivalent to change rate), displaying data to the user, independent relations (appears equivalent to base contribution), and influence to other data (appears equivalent to relational contribution. Many of the similar aspects to the current application appear in the claims of JP 201456448A.
Akiyama Sayaka et al (JP 2019036061A) is considered relevant art, as the reference covers analysis of causal systems including influence degree or degree of influence for direct and indirect connections through edges in a causal graph.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
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/C.D.D./Examiner, Art Unit 2129
/MICHAEL J HUNTLEY/Supervisory Patent Examiner, Art Unit 2129