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 .
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 6-10, 11-13 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 6:
Claim 6 recites the limitation "wherein the first value node is the at least one of the one or more value nodes of the graph-based model and the second value node is a target value node”. This claim is considered indefinite, as one of ordinary skill cannot ascertain what the first value node is being considered. Is the limitation trying to define the “at least one of the one or more value nodes” as being “the first value node”? Defining “at least one” to only one node could create an issue of trying to understand whether the broader aspect (at least one) or narrower aspect (only one node or “the first value node”) are claimed. For prior art investigation the claim is interpretated as indicating the at least one of the one or more value nodes includes the first value node.
In regard to Claim 11:
Claim 11 recites the limitation "wherein the overlay node is associated with a first context and the further overlay node is associated with a second context”. There is insufficient antecedent basis for this limitation in the claim. There is no previous recitation of “an overlay node”. Claim 1 notes “a rule overlay node” and claim 11 notes “a further overlay node”, but one cannot determine whether “the overlay node” refers to either of the two existing overlay nodes or to a new overlay node. Appropriate correction is required. For prior art examination, the claim is interpreted as indicating there is multiple overlay nodes, where “the overlay node” is interpreted as “the rule overlay node” to mean the rule overlay node is for one context and the further overlay node is for a second context.
In regard to dependent claims:
Claims dependent upon a rejected claim under 112(b) are also rejected for being dependent on a rejected limitation.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed towards an abstract idea without significantly more.
Claim 1:
Step 1: Is the claim directed towards a process, machine, manufacture, or composition of matter?
Yes, the claim is directed towards a system, so 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 1 recites the following abstract ideas:
wherein execution of the executable inference hypergraph includes an execution of the first executable inference rule to evaluate the first inference rule using the set of terms encapsulated by the first hyperedge.
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 the limitation 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 1 recites the following additional elements:
A system comprising: a memory storing: a graph-based model comprising one or more value nodes storing one or more values;
At a high level of generality, this is an Insignificant extra-solution activity of mere data gathering or outputting (MPEP 2106.05(g)).
and an executable inference hypergraph representing a rule-based model, wherein the executable inference hypergraph comprises: a first hyperedge associated with a first inference rule of the rule-based model and encapsulating a plurality of value nodes storing a plurality of values such that the plurality of values form a part of a set of terms used to evaluate the first inference rule, wherein the plurality of value nodes include at least one of the one or more value nodes of the graph-based model; and a rule overlay node coupled to the first hyperedge thereby forming a first executable inference rule, wherein the rule overlay node comprises processing logic operable to evaluate the first inference rule using the set of terms encapsulated by the first hyperedge;
At a high level of generality, this is an Insignificant extra-solution activity of mere data gathering or outputting (MPEP 2106.05(g)).
and processing circuitry coupled to the memory and configured to:
At a high level of generality, this is an activity of using a computer as an “apply it” use (see MPEP 2106.05(f)).
receive a trigger related to a request to perform an inference using the executable inference hypergraph;
This limitation is directed towards the insignificant extra solution activity of mere data gathering (see MPEP § 2106.05(g)).
and in response to the trigger being received, execute the executable inference hypergraph to determine an inference outcome,
At a high level of generality, this is an activity of using an element as an “apply it” use (see MPEP 2106.05(f)).
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 1 recites the following additional elements:
A system comprising: a memory storing: a graph-based model comprising one or more value nodes storing one or more values;
At a high level of generality, this is an Insignificant extra-solution activity of mere data gathering or outputting (MPEP 2106.05(g)). This is a well understood, routine, conventional activity of storing data (see MPEP 2106.05(d) example iv in computer functions).
and an executable inference hypergraph representing a rule-based model, wherein the executable inference hypergraph comprises: a first hyperedge associated with a first inference rule of the rule-based model and encapsulating a plurality of value nodes storing a plurality of values such that the plurality of values form a part of a set of terms used to evaluate the first inference rule, wherein the plurality of value nodes include at least one of the one or more value nodes of the graph-based model; and a rule overlay node coupled to the first hyperedge thereby forming a first executable inference rule, wherein the rule overlay node comprises processing logic operable to evaluate the first inference rule using the set of terms encapsulated by the first hyperedge;
At a high level of generality, this is an Insignificant extra-solution activity of mere data gathering or outputting (MPEP 2106.05(g)). This is a well understood, routine, conventional activity of storing data (see MPEP 2106.05(d) example iv in computer functions). Storing values in nodes which are stored in memory is seen as storing values.
and processing circuitry coupled to the memory and configured to:
At a high level of generality, this is an activity of using a computer as an “apply it” use (see MPEP 2106.05(f)). At said high level of generality, a computer or 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.
receive a trigger related to a request to perform an inference using the executable inference hypergraph;
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 in response to the trigger being received, execute the executable inference hypergraph to determine an inference outcome,
At a high level of generality, this is an activity of using an element as an “apply it” use (see MPEP 2106.05(f)). At said high level of generality, a generic recitation of “apply” or equivalent does not incorporate the abstract idea into a practical invention and is seen as a variation of the phrase “apply it”. This limitation is seen as applying the inference hypergraph.
Claim 2:
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 2 recites the following additional elements:
wherein the first hyperedge further encapsulates a second hyperedge associated with a second inference rule of the rule- based model.
At a high level of generality, this is a continuation of an Insignificant extra-solution activity of mere data gathering or outputting (MPEP 2106.05(g)) in claim 1.
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 2 recites the following additional elements:
wherein the first hyperedge further encapsulates a second hyperedge associated with a second inference rule of the rule- based model.
At a high level of generality, this is a continuation of an Insignificant extra-solution activity of mere data gathering or outputting (MPEP 2106.05(g)) in claim 1. The storing of data is a well understood, routine, conventional activity of storing data (see MPEP 2106.05(d) example iv in computer functions). Describing the structure or other aspects of the stored elements does not integrate into a practical application.
Claim 3:
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 3 recites the following additional elements:
wherein the set of terms used to evaluate the first inference rule include an outcome value of the second hyperedge or the second inference rule of the second hyperedge.
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 3 recites the following additional elements:
wherein the set of terms used to evaluate the first inference rule include an outcome value of the second hyperedge or the second inference rule of the second hyperedge.
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).
Claim 4:
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 4 recites the following abstract ideas:
the first inference rule implemented by the processing logic of the rule overlay node outputs a Boolean value based on a comparison of values of a first of the plurality of value nodes and a second of the plurality of value nodes.
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 the limitation is seen as evaluation and judgement.
Claim 5:
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 5 recites the following additional elements:
wherein a first value node of the plurality of value nodes is assigned to a first role of the first hyperedge and a second value node of the plurality of value nodes is assigned to a second role of the first hyperedge, wherein the first role associates the first value node with a first side of the first inference rule and the second role associates the second value node with a second side of the first inference rule.
At a high level of generality, this is a continuation of an Insignificant extra-solution activity of mere data gathering or outputting (MPEP 2106.05(g)) in claim 1.
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 5 recites the following additional elements:
wherein a first value node of the plurality of value nodes is assigned to a first role of the first hyperedge and a second value node of the plurality of value nodes is assigned to a second role of the first hyperedge, wherein the first role associates the first value node with a first side of the first inference rule and the second role associates the second value node with a second side of the first inference rule.
At a high level of generality, this is a continuation of an Insignificant extra-solution activity of mere data gathering or outputting (MPEP 2106.05(g)) in claim 1. The storing of data is a well understood, routine, conventional activity of storing data (see MPEP 2106.05(d) example iv in computer functions). Describing the structure or other aspects of the stored elements does not integrate into a practical application.
Claim 6:
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 6 recites the following additional elements:
wherein the first value node is the at least one of the one or more value nodes of the graph-based model and the second value node is a target value node
At a high level of generality, this is a continuation of an Insignificant extra-solution activity of mere data gathering or outputting (MPEP 2106.05(g)) in claim 5.
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 6 recites the following additional elements:
wherein the first value node is the at least one of the one or more value nodes of the graph-based model and the second value node is a target value node
At a high level of generality, this is a continuation of an Insignificant extra-solution activity of mere data gathering or outputting (MPEP 2106.05(g)) in claim 5. The storing of data is a well understood, routine, conventional activity of storing data (see MPEP 2106.05(d) example iv in computer functions). Describing the structure or other aspects of the stored elements does not integrate into a practical application.
Claim 7:
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 7 recites the following additional elements:
wherein the first side is a left-hand-side (LHS) of the first inference rule and the second side is a right-hand-side (RHS) of the first inference rule
At a high level of generality, this is a continuation of an Insignificant extra-solution activity of mere data gathering or outputting (MPEP 2106.05(g)) in claim 5.
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 7 recites the following additional elements:
wherein the first side is a left-hand-side (LHS) of the first inference rule and the second side is a right-hand-side (RHS) of the first inference rule
At a high level of generality, this is a continuation of an Insignificant extra-solution activity of mere data gathering or outputting (MPEP 2106.05(g)) in claim 5. The storing of data is a well understood, routine, conventional activity of storing data (see MPEP 2106.05(d) example iv in computer functions). Describing the structure or other aspects of the stored elements does not integrate into a practical application.
Claim 8:
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 8 recites the following additional elements:
wherein the LHS of the first inference rule is associated with a conditional statement and the RHS of the first inference rule is associated with an outcome of the conditional statement
At a high level of generality, this is a continuation of an Insignificant extra-solution activity of mere data gathering or outputting (MPEP 2106.05(g)) in claim 7.
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 8 recites the following additional elements:
wherein the LHS of the first inference rule is associated with a conditional statement and the RHS of the first inference rule is associated with an outcome of the conditional statement
At a high level of generality, this is a continuation of an Insignificant extra-solution activity of mere data gathering or outputting (MPEP 2106.05(g)) in claim 7. The storing of data is a well understood, routine, conventional activity of storing data (see MPEP 2106.05(d) example iv in computer functions). Describing the structure or other aspects of the stored elements does not integrate into a practical application.
Claim 9:
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 9 recites the following additional elements:
the first hyperedge further encapsulates a third value node which is assigned to the first role of the first hyperedge
At a high level of generality, this is a continuation of an Insignificant extra-solution activity of mere data gathering or outputting (MPEP 2106.05(g)) in claim 8.
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 9 recites the following additional elements:
the first hyperedge further encapsulates a third value node which is assigned to the first role of the first hyperedge
At a high level of generality, this is a continuation of an Insignificant extra-solution activity of mere data gathering or outputting (MPEP 2106.05(g)) in claim 8. The storing of data is a well understood, routine, conventional activity of storing data (see MPEP 2106.05(d) example iv in computer functions). Describing the structure or other aspects of the stored elements does not integrate into a practical application.
Claim 10:
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 10 recites the following abstract ideas:
wherein the first inference rule implemented by the processing logic of the rule overlay node outputs a value of the second value node based on a satisfaction of the conditional statement involving values of the first value node and the third value node
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 the limitation is seen as evaluation and judgement.
Claim 11:
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 11 recites the following additional elements:
wherein the first executable inference rule comprises a further overlay node comprising processing logic operable to evaluate the first inference rule, wherein the overlay node is associated with a first context and the further overlay node is associated with a second context
At a high level of generality, this is a continuation of an Insignificant extra-solution activity of mere data gathering or outputting (MPEP 2106.05(g)) in claim 1.
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 11 recites the following additional elements:
wherein the first executable inference rule comprises a further overlay node comprising processing logic operable to evaluate the first inference rule, wherein the overlay node is associated with a first context and the further overlay node is associated with a second context
At a high level of generality, this is a continuation of an Insignificant extra-solution activity of mere data gathering or outputting (MPEP 2106.05(g)) in claim 1. The storing of data is a well understood, routine, conventional activity of storing data (see MPEP 2106.05(d) example iv in computer functions). Describing the structure or other aspects of the stored elements does not integrate into a practical application.
Claim 12:
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 12 recites the following abstract ideas:
wherein the executable inference hypergraph is executed according to a received context such that the first executable inference rule is executed based on the received context
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 the limitation is seen as evaluation.
Claim 13:
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 13 recites the following abstract ideas:
wherein the overlay node is executed when the first context matches the received context and the further overlay node is executed when the second context matches the received context.
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 the limitation is seen as evaluation.
Claim 14:
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 14 recites the following abstract ideas:
wherein the first inference rule implemented by the processing logic of the rule overlay node outputs a weight value indicative of a degree of certainty in an evaluation of the first inference rule
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 the limitation is seen as evaluation.
Claim 15:
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 15 recites the following abstract ideas:
wherein execution of the executable inference hypergraph further determines an inference certainty indicative of a combined degree of certainty in an evaluation of one or more inference rules of the executable inference hypergraph
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 the limitation is seen as evaluation.
Claim 16:
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 16 recites the following abstract ideas:
wherein the processing circuitry is configured as part of execution of the executable inference hypergraph to: compare the weight value to a threshold certainty value;
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 the limitation is seen as evaluation and judgement.
when the weight value does not satisfy the threshold certainty value, obtain an additional term such that the first inference rule is re-evaluated using the set of terms and the additional term.
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 the limitation is seen as evaluation.
Claim 17:
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 17 recites the following additional elements:
wherein the additional term is obtained from a user of the system.
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 17 recites the following additional elements:
wherein the additional term is obtained from a user of the system.
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).
Claim 18:
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:
wherein the memory further stores an inference hypergraph template from which the executable inference hypergraph is generated
At a high level of generality, this is an Insignificant extra-solution activity of mere data gathering or outputting (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 18 recites the following additional elements:
wherein the memory further stores an inference hypergraph template from which the executable inference hypergraph is generated
At a high level of generality, this is an Insignificant extra-solution activity of mere data gathering or outputting (MPEP 2106.05(g)). This is a well understood, routine, conventional activity of storing data (see MPEP 2106.05(d) example iv in computer functions).
Claim 19:
Step 1: Is the claim directed towards a process, machine, manufacture, or composition of matter?
Yes, the claim 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 19 recites the following abstract ideas:
A method comprising: identifying, using processing circuitry, a graph-based model comprising one or more value nodes storing one or more values;
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 the limitation is seen as evaluation.
identifying, using the processing circuitry, an executable inference hypergraph representing a rule-based model, wherein the executable inference hypergraph comprises a first hyperedge associated with a first inference rule of the rule-based model and encapsulating a plurality of value nodes storing a plurality of values such that the plurality of values form a part of a set of terms used to evaluate the first inference rule, wherein the plurality of value nodes include at least one of the one or more value nodes of the graph-based model, and a rule overlay node coupled to the first hyperedge thereby forming a first executable inference rule, wherein the rule overlay node comprises processing logic operable to evaluate the first inference rule using the set of terms encapsulated by the first hyperedge;
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 the limitation is seen as evaluation.
wherein execution of the executable inference hypergraph includes an execution of the first executable inference rule to evaluate the first inference rule using the set of terms encapsulated by the first hyperedge
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 the limitation 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 19 recites the following additional elements:
receiving, by the processing circuitry, a trigger related to a request to perform an inference using the executable inference hypergraph;
This limitation is directed towards the insignificant extra solution activity of mere data gathering (see MPEP § 2106.05(g)).
and in response to the trigger being received, executing, by the processing circuitry, the executable inference hypergraph to determine an inference outcome,
At a high level of generality, this is an activity of using an element as an “apply it” use (see MPEP 2106.05(f)).
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, by the processing circuitry, a trigger related to a request to perform an inference using the executable inference hypergraph;
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 in response to the trigger being received, executing, by the processing circuitry, the executable inference hypergraph to determine an inference outcome,
At a high level of generality, this is an activity of using an element as an “apply it” use (see MPEP 2106.05(f)). At said high level of generality, a generic recitation of “apply” or equivalent does not incorporate the abstract idea into a practical invention and is seen as a variation of the phrase “apply it”. This limitation is seen as applying the inference hypergraph.
Claim 20:
This claim is analogous to claim 19.
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 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over:
Wang et al (US 20160328433 A1), referred to as Wang in this document,
Lincoln et al (US 20030033126 A1), referred to as Lincoln in this document,
Dutkowski (US 20190005395), referred to as Dutkowski in this document,
Qi et al (US 20220017032A1), referred to as Qi in this document,
Rowe et al (US 20220366280), referred to as Rowe in this document.
Claims 1-10, 14, 15, 19, 20 are rejected under Wang and Lincoln.
Claim 1:
Wang teaches:
A system comprising: a memory storing:
[Wang 0087]: “Examples of computer readable media include but are not limited to: nonvolatile, hard-coded type media such as read only memories (ROMs), CD-ROMs, and DVD-ROMs, or erasable, electrically programmable read only memories (EEPROMs), recordable type media such as floppy disks, hard disk drives, CD-R/RWs, DVD-RAMs, DVD-R/RWs, DVD+R/RWs, flash drives, memory sticks [A system comprising: a memory storing], and other newer types of memories, and transmission type media such as digital and analog communication links. For example, such media can include or contain operating instructions stored therein/thereon, as well as instructions or instruction sets related to the system and particular method steps described above, and can operate on a computer by way of processing unit execution. It will be understood by those skilled in the art that such media can be at other locations instead of or in addition to a file management computer server to store program products, e.g., including software, thereon.”
a graph-based model comprising one or more value nodes storing one or more values;
[Wang 0052]: “It is noted that in the present disclosure, the association between the vertices represented by a hyperedge does not have to be a pattern, a statistically significant pattern, or statistical pattern. Any kind of association, even any pair of variables and its value [a graph-based model comprising one or more value nodes storing one or more values] found in the data set may be represented as vertices. In other words, all the data events found in a given data set can be or are collected and represented as vertices. As will be described later, this enables embodiments in accordance with the present disclosure to provide a method for further analysis such as manipulation and retrieval of data from the data set.”
and an executable inference hypergraph representing a rule-based model,
[Wang 0029]: “First, because patterns that induce more than two events are a major concern, a framework which is capable of representing the relationships among multiple events has to be used. Second, in probability inference [and an executable inference hypergraph representing a rule-based model] and many other AI techniques, network representations are extensively used. Networks are graphs which can be considered a special case of a hypergraph. Networks explicitly show the relationships between two nodes.”
Support for there being rules is given in [Wang 0009]: “Production (if-then) rule is another scheme widely used in expert systems and classification oriented tasks. It explicitly presents the association between a set of observations (left-hand antecedent) and one attribute value (right-hand consequent). Rules are considered easier to understand than trees”
Support for executable is given by Wang indicating the hypergraph can be used or queried, which is interpreted as a way of executing or using the hypergraph ([Wang 0036]: “In an embodiment according to the present disclosure, data relationships may be stored as attributed hypergraphs in a computer or computer network, ready for querying and further analysis.”).
wherein the executable inference hypergraph comprises: a first hyperedge associated with a first inference rule of the rule-based model
[Wang 0009]: “Production (if-then) rule [wherein the executable inference hypergraph comprises: a first hyperedge associated with a first inference rule of the rule-based model] is another scheme widely used in expert systems and classification oriented tasks. It explicitly presents the association between a set of observations (left-hand antecedent) and one attribute value (right-hand consequent). Rules are considered easier to understand than trees”
Further support of hyperedge is provided in [Wang 0032]: “The hyperedges are sets that show the associations among their elements which can also be sets.”
and encapsulating a plurality of value nodes storing a plurality of values such that the plurality of values form a part of a set of terms used to evaluate the first inference rule
wherein the plurality of value nodes include at least one of the one or more value nodes of the graph-based model
[Wang 0052]: “It is noted that in the present disclosure, the association between the vertices represented by a hyperedge does not have to be a pattern, a statistically significant pattern, or statistical pattern. Any kind of association, even any pair of variables and its value [and encapsulating a plurality of value nodes storing a plurality of values such that the plurality of values form a part of a set of terms used to evaluate the first inference rule, wherein the plurality of value nodes include at least one of the one or more value nodes of the graph-based model] found in the data set may be represented as vertices. In other words, all the data events found in a given data set can be or are collected and represented as vertices. As will be described later, this enables embodiments in accordance with the present disclosure to provide a method for further analysis such as manipulation and retrieval of data from the data set.”
Further support of hyperedge and values forming a set is provided in [Wang 0032]: “In the attributed hypergraph representation according to the present disclosure, however, higher order relations are not induced by lower order relations. This representation does not depend on pairwise links. The hyperedges are sets that show the associations among their elements which can also be sets. Yet, the basic element of the proposed hypergraph representation is not a variable but a primary event or data event. That is, dependencies occur among events and not variables. In the bell-coin experiment, if the bell can make 3 kinds of sounds, only the first kind of sound, for instance, beep twice, indicates whether or not the outcomes of the two coins are the same. Other signals have nothing to do with the coins (e.g., perhaps they indicate situations of other events.) It is the event [B=beep twice], not B, that relates the outcomes of the coins. In hypergraph representation, the hyperedges of [B=beep twice; C1=head; C2=head] and [B=beep twice; C1=tail; C2=tail] show the relationships among them.”
Hyperedges, as noted in the above quote, indicate associations between elements and Wang also notes associations and such can be represented by rules/conditions in [Wang 0009]: “Production (if-then) rule is another scheme widely used in expert systems and classification oriented tasks. It explicitly presents the association between a set of observations (left-hand antecedent) and one attribute value (right-hand consequent). Rules are considered easier to understand than trees”
Wang does not explicitly teach:
and a rule overlay node coupled to the first hyperedge thereby forming a first executable inference rule, wherein the rule overlay node comprises processing logic operable to evaluate the first inference rule using the set of terms encapsulated by the first hyperedge;
Wang teaches rules [Wang 0009], and as indicated earlier in claim 1, the rules are associated with edges.
Lincoln teaches:
[Lincoln 0024]: “In still another aspect, the invention features a method of evaluating a rule [and a rule overlay node coupled to the first hyperedge thereby forming a first executable inference rule, wherein the rule overlay node comprises processing logic operable to evaluate the first inference rule using the set of terms encapsulated by the first hyperedge] describing an interaction between elements of a biological system. The method includes: receiving in an inference engine (1) at least first and second sets of symbols, representing hypothetical first and second states of a biological system, the symbols representing biological elements of the biological system and (2) rules that express a substitution of symbols representing biological elements by other symbols representing biological elements; and either determining if one or more of the rules must be true or false for the first state to reach the second state by processing the first state using the rules or determining if the first state can reach or progress to the second state given the rules. For example, the method uses a theorem prover to prove or disprove a theory, e.g., a theory implicit in a contemplated rule. The proof may depend on the interrelationship of the first state with the second state. The hypothetical first and second states may represent different cells, e.g., a normal cell or a cell with a precondition, disease or disorder. If a rule must be true for the biological system to progress from the first state to the second state, the operands of the rule may identify elements of the biological system that are drug targets. For example, preventing the element represented by one of the operands from functioning is likely to prevent the biological system from progressing from the first (e.g., normal) state to the second state (e.g., a diseased state).”
Support for the connection to how wang does rules is given by Lincoln also having a similar if then setup for rules in [Lincoln 0079-0082]. Lincoln is showing/teaching that rules are evaluated to determine if the rules are met, thus is showing an executable inference rule that contains “logic operable to evaluate the first inference rule using the set of terms encapsulated by the first hyperedge” as Lincoln is evaluating the rule for an edge. As a result, Lincoln is seen as teaching the required aspects for “a rule overlay node” as the elements of the node are taught. The rule being coupled to the edge is indicated by the rule being associated with the edge and being the requirement for traversing the edge.
[Lincoln 0079-0082]: "Conditional rules are used to express a substitution of symbols that only occurs when a condition is met. The condition can be expressed as an "if" statement. The "if" statement is evaluated first, and, if true, the rewriting rule is performed. The use of typing enhances the capacity and expressiveness of rewriting rule statements. For example, if proteins M and N are of type A, then the rewriting rule A.fwdarw.A B is evaluated as follows: given "M", the rewriting rule produces "M B"; given "N", the rewriting rule produces "N B." Thus, symbols that are declared to be of type A (or a subtype thereof), are evaluated as A by the rule.".
Without particular recitations on how the coupling of an overlay node to an edge is done within the claims, under BRI the coupling can be one of many methods to show an aspect of relation or connection between elements.
Wang continues to teach:
and processing circuitry coupled to the memory and configured to:
[Wang 0086]: “Multi-processor [and processing circuitry coupled to the memory and configured to:] computers, cloud computing, server farms, multiple computer systems, multiple databases and storage devices (including hierarchies of storage and access), and other implementations will be recognized by those having skill in the art as encompassed within the scope of embodiments of the present disclosure.”
receive a trigger related to a request to perform an inference using the executable inference hypergraph; and in response to the trigger being received, execute the executable inference hypergraph to determine an inference outcome,
[Wang 0036]: “In an embodiment according to the present disclosure, data relationships may be stored as attributed hypergraphs in a computer or computer network, ready for querying [receive a trigger related to a request to perform an inference using the executable inference hypergraph; and in response to the trigger being received, execute the executable inference hypergraph to determine an inference outcome,] and further analysis.”
Aspects related to executable and inference are explained earlier in claim 1.
Wang does not explicitly teach:
wherein execution of the executable inference hypergraph includes an execution of the first executable inference rule to evaluate the first inference rule using the set of terms encapsulated by the first hyperedge
Wang indicates the utilization of hypergraphs for things such as search/retrieval ([Wang 0022]: “receiving criteria; retrieving vertices and/or hyperedges associated with the criteria; and outputting search results.”)
Lincoln teaches:
[Lincoln 0024]: “The method includes: receiving in an inference engine (1) at least first and second sets of symbols, representing hypothetical first and second states of a biological system, the symbols representing biological elements of the biological system and (2) rules that express a substitution of symbols representing biological elements by other symbols representing biological elements; and either determining if one or more of the rules must be true or false for the first state to reach the second state by processing the first state using the rules [wherein execution of the executable inference hypergraph includes an execution of the first executable inference rule to evaluate the first inference rule using the set of terms encapsulated by the first hyperedge] or determining if the first state can reach or progress to the second state given the rules.”
One of ordinary skill in the art, prior to the effective filing date, would have been motivated to combine Wang and Lincoln. Wang and Lincoln are in the same field of endeavor of graphs, such as hypergraphs. Lincoln’s connection to hypergraphs is shown in paragraph 11 ([Lincoln 0011]: “The method can further include representing biological states as vectors of logical properties. The method can further include processing the rules using a model checker. It can further include displaying a representation of a decision diagram. It can further include displaying a wiring diagram, e.g., as a hypergraph, and, optionally, computing the transititive closure of that hypergraph.”). One of ordinary skill in the art would have been motivated to combine Wang and Lincoln in order to further support the teaching of utilizing rules in the execution of rules for ensuring a rule/condition is met ([Lincoln 0024]: “The method includes: receiving in an inference engine (1) at least first and second sets of symbols, representing hypothetical first and second states of a biological system, the symbols representing biological elements of the biological system and (2) rules that express a substitution of symbols representing biological elements by other symbols representing biological elements; and either determining if one or more of the rules must be true or false for the first state to reach the second state by processing the first state using the or determining if the first state can reach or progress to the second state given the rules.”).
Claim 2:
The system of claim 1 is taught by Wang, Lincoln
Wang teaches:
wherein the first hyperedge further encapsulates a second hyperedge associated with a second inference rule of the rule- based model
[Wang 0032]: “In the attributed hypergraph representation according to the present disclosure, however, higher order relations are not induced by lower order relations. This representation does not depend on pairwise links. The hyperedges are sets that show the associations among their elements which can also be sets. Yet, the basic element of the proposed hypergraph representation is not a variable but a primary event or data event. That is, dependencies occur among events and not variables. In the bell-coin experiment, if the bell can make 3 kinds of sounds, only the first kind of sound, for instance, beep twice, indicates whether or not the outcomes of the two coins are the same. Other signals have nothing to do with the coins (e.g., perhaps they indicate situations of other events.) It is the event [B=beep twice], not B, that relates the outcomes of the coins. In hypergraph representation, the hyperedges [wherein the first hyperedge further encapsulates a second hyperedge associated with a second inference rule of the rule- based model as Wang is teaching there can be multiple hyperedges] of [B=beep twice; C1=head; C2=head] and [B=beep twice; C1=tail; C2=tail] show the relationships among them.”
Claim 3:
The system of claim 2 is taught by Wang, Lincoln
Wang teaches:
wherein the set of terms used to evaluate the first inference rule include an outcome value of the second hyperedge or the second inference rule of the second hyperedge
[Wang 0032]: “In the attributed hypergraph representation according to the present disclosure, however, higher order relations are not induced by lower order relations. This representation does not depend on pairwise links. The hyperedges are sets that show the associations among their elements which can also be sets. Yet, the basic element of the proposed hypergraph representation is not a variable but a primary event or data event. That is, dependencies occur among events and not variables. In the bell-coin experiment, if the bell can make 3 kinds of sounds, only the first kind of sound, for instance, beep twice, indicates whether or not the outcomes of the two coins are the same. Other signals have nothing to do with the coins (e.g., perhaps they indicate situations of other events.) It is the event [B=beep twice], not B, that relates the outcomes of the coins. In hypergraph representation, the hyperedges [wherein the set of terms used to evaluate the first inference rule include an outcome value of the second hyperedge or the second inference rule of the second hyperedge as Wang is teaching there can be multiple hyperedges and the hyper edges have outcomes] of [B=beep twice; C1=head; C2=head] and [B=beep twice; C1=tail; C2=tail] show the relationships among them.”
Further support of there being outcomes for hyperedges is given in [Wang 0009]: “Production (if-then) rule is another scheme widely used in expert systems and classification oriented tasks. It explicitly presents the association between a set of observations (left-hand antecedent) and one attribute value (right-hand consequent). Rules are considered easier to understand than trees. However, in KDD applications, with each changing interest, the values of different attributes have to be predicted. Besides, a huge number of rules have to be obtained. This is sometimes impractical in the real world. See a paper by A. K. C. Wong and Y. Wang, entitled “High order pattern discovery from discrete-valued data,” IEEE Trans. On Knowledge and Data Engineering, 9(6):877-893, 1997. In this case, we need a scheme which can easily re-organize the represented knowledge for different goals of the system.”
Claim 4:
The system of claim 1 is taught by Wang, Lincoln
Lincoln teaches:
wherein the first inference rule implemented by the processing logic of the rule overlay node outputs a Boolean value based on a comparison of values of a first of the plurality of value nodes and a second of the plurality of value nodes
[Lincoln 0024]: “In still another aspect, the invention features a method of evaluating a rule describing an interaction between elements of a biological system. The method includes: receiving in an inference engine (1) at least first and second sets of symbols, representing hypothetical first and second states of a biological system, the symbols representing biological elements of the biological system and (2) rules that express a substitution of symbols representing biological elements by other symbols representing biological elements; and either determining if one or more of the rules must be true or false [wherein the first inference rule implemented by the processing logic of the rule overlay node outputs a Boolean value based on a comparison of values of a first of the plurality of value nodes and a second of the plurality of value nodes] for the first state to reach the second state by processing the first state using the rules or determining if the first state can reach or progress to the second state given the rules. For example, the method uses a theorem prover to prove or disprove a theory, e.g., a theory implicit in a contemplated rule. The proof may depend on the interrelationship of the first state with the second state. The hypothetical first and second states may represent different cells, e.g., a normal cell or a cell with a precondition, disease or disorder. If a rule must be true for the biological system to progress from the first state to the second state, the operands of the rule may identify elements of the biological system that are drug targets. For example, preventing the element represented by one of the operands from functioning is likely to prevent the biological system from progressing from the first (e.g., normal) state to the second state (e.g., a diseased state).”
The motivation to combine with Lincoln is the same as claim 1.
Claim 5:
The system of claim 1 is taught by Wang, Lincoln
Wang teaches:
wherein a first value node of the plurality of value nodes is assigned to a first role of the first hyperedge and a second value node of the plurality of value nodes is assigned to a second role of the first hyperedge, wherein the first role associates the first value node with a first side of the first inference rule and the second role associates the second value node with a second side of the first inference rule
[Wang 0009]: “Production (if-then) rule is another scheme widely used in expert systems and classification oriented tasks. It explicitly presents the association between a set of observations (left-hand antecedent) and one attribute value (right-hand consequent) [wherein a first value node of the plurality of value nodes is assigned to a first role of the first hyperedge and a second value node of the plurality of value nodes is assigned to a second role of the first hyperedge, wherein the first role associates the first value node with a first side of the first inference rule and the second role associates the second value node with a second side of the first inference rule as Wang is indicating there is a left hand side and right hand side (thus two sides of the rule)]. Rules are considered easier to understand than trees. However, in KDD applications, with each changing interest, the values of different attributes have to be predicted. Besides, a huge number of rules have to be obtained. This is sometimes impractical in the real world. See a paper by A. K. C. Wong and Y. Wang, entitled “High order pattern discovery from discrete-valued data,” IEEE Trans. On Knowledge and Data Engineering, 9(6):877-893, 1997. In this case, we need a scheme which can easily re-organize the represented knowledge for different goals of the system.”
Claim 6:
The system of claim 5 is taught by Wang, Lincoln
Wang teaches:
wherein the first value node is the at least one of the one or more value nodes of the graph-based model and the second value node is a target value node
[Wang 0009]: “Production (if-then) rule is another scheme widely used in expert systems and classification oriented tasks. It explicitly presents the association between a set of observations (left-hand antecedent) and one attribute value (right-hand consequent) [wherein the first value node is the at least one of the one or more value nodes of the graph-based model and the second value node is a target value node as Wang is indicating there is a left hand side and right hand side thus a node of the model on the left can be the value and the node on the right can be the target.]. Rules are considered easier to understand than trees. However, in KDD applications, with each changing interest, the values of different attributes have to be predicted. Besides, a huge number of rules have to be obtained. This is sometimes impractical in the real world. See a paper by A. K. C. Wong and Y. Wang, entitled “High order pattern discovery from discrete-valued data,” IEEE Trans. On Knowledge and Data Engineering, 9(6):877-893, 1997. In this case, we need a scheme which can easily re-organize the represented knowledge for different goals of the system.”
The first value node is a part of the base model as the edge with the rule would be in the hypergraph. Hypergraphs contain hyperedges as indicated by Wang in claim 1.
More information should be added to claim to indicate what being a target value node means should the current interpretation seem broad as a result of using BRI.
Claim 7:
The system of claim 5 is taught by Wang, Lincoln
Wang teaches:
wherein the first side is a left-hand-side (LHS) of the first inference rule and the second side is a right-hand-side (RHS) of the first inference rule
[Wang 0009]: “Production (if-then) rule is another scheme widely used in expert systems and classification oriented tasks. It explicitly presents the association between a set of observations (left-hand antecedent) and one attribute value (right-hand consequent) [wherein the first side is a left-hand-side (LHS) of the first inference rule and the second side is a right-hand-side (RHS) of the first inference rule]. Rules are considered easier to understand than trees. However, in KDD applications, with each changing interest, the values of different attributes have to be predicted. Besides, a huge number of rules have to be obtained. This is sometimes impractical in the real world. See a paper by A. K. C. Wong and Y. Wang, entitled “High order pattern discovery from discrete-valued data,” IEEE Trans. On Knowledge and Data Engineering, 9(6):877-893, 1997. In this case, we need a scheme which can easily re-organize the represented knowledge for different goals of the system.”
Claim 8:
The system of claim 7 is taught by Wang, Lincoln
Wang teaches:
wherein the LHS of the first inference rule is associated with a conditional statement and the RHS of the first inference rule is associated with an outcome of the conditional statement
[Wang 0009]: “Production (if-then) rule is another scheme widely used in expert systems and classification oriented tasks. It explicitly presents the association between a set of observations (left-hand antecedent) and one attribute value (right-hand consequent) [wherein the LHS of the first inference rule is associated with a conditional statement and the RHS of the first inference rule is associated with an outcome of the conditional statement where further support of the condition is shown by the indication of “if-then” rule at beginning of quote]. Rules are considered easier to understand than trees. However, in KDD applications, with each changing interest, the values of different attributes have to be predicted. Besides, a huge number of rules have to be obtained. This is sometimes impractical in the real world. See a paper by A. K. C. Wong and Y. Wang, entitled “High order pattern discovery from discrete-valued data,” IEEE Trans. On Knowledge and Data Engineering, 9(6):877-893, 1997. In this case, we need a scheme which can easily re-organize the represented knowledge for different goals of the system.”
Claim 9:
The system of claim 8 is taught by Wang, Lincoln
Wang teaches:
wherein the first hyperedge further encapsulates a third value node which is assigned to the first role of the first hyperedge
[Wang 0009]: “Production (if-then) rule is another scheme widely used in expert systems and classification oriented tasks. It explicitly presents the association between a set of observations [wherein the first hyperedge further encapsulates a third value node which is assigned to the first role of the first hyperedge as multiple values are noted to be supported (indicated by observations being plural)] (left-hand antecedent) and one attribute value (right-hand consequent) Rules are considered easier to understand than trees. However, in KDD applications, with each changing interest, the values of different attributes have to be predicted. Besides, a huge number of rules have to be obtained. This is sometimes impractical in the real world. See a paper by A. K. C. Wong and Y. Wang, entitled “High order pattern discovery from discrete-valued data,” IEEE Trans. On Knowledge and Data Engineering, 9(6):877-893, 1997. In this case, we need a scheme which can easily re-organize the represented knowledge for different goals of the system.”
Additional support for multiple nodes is given in [Wang 0033]: “Different sizes of the hyperedges reflect different levels of generalization. The larger the number of vertices in a hyperedge, the more details a concept (pattern) contains. The hyperedges of smaller sizes often represent more generalized concepts (or patterns). One advantage of the hypergraph representation is that it allows easy movement among different levels of generality, which cannot be done (or only with great difficulty) by graph or network representations.”
Claim 10:
The system of claim 9 is taught by Wang, Lincoln
Wang teaches:
wherein the first inference rule implemented by the processing logic of the rule overlay node outputs a value of the second value node based on a satisfaction of the conditional statement involving values of the first value node and the third value node
[Wang 0032]: “In the attributed hypergraph representation according to the present disclosure, however, higher order relations are not induced by lower order relations. This representation does not depend on pairwise links. The hyperedges are sets that show the associations among their elements which can also be sets. Yet, the basic element of the proposed hypergraph representation is not a variable but a primary event or data event. That is, dependencies occur among events and not variables. In the bell-coin experiment, if the bell can make 3 kinds of sounds, only the first kind of sound, for instance, beep twice, indicates whether or not the outcomes of the two coins are the same. Other signals have nothing to do with the coins (e.g., perhaps they indicate situations of other events.) It is the event [B=beep twice], not B, that relates the outcomes of the coins [wherein the first inference rule implemented by the processing logic of the rule overlay node outputs a value of the second value nod as this example shows the hyperedges and the relations of the hyperedges indicate an outcome given input ]. In hypergraph representation, the hyperedges of [B=beep twice; C1=head; C2=head] and [B=beep twice; C1=tail; C2=tail] show the relationships among them.”
[Wang 0009]: “Production (if-then) rule is another scheme widely used in expert systems and classification oriented tasks. It explicitly presents the association between a set of observations [node based on a satisfaction of the conditional statement involving values of the first value node and the third value node where support for multiple node inputs is shown in claim 9] (left-hand antecedent) and one attribute value (right-hand consequent) Rules are considered easier to understand than trees. However, in KDD applications, with each changing interest, the values of different attributes have to be predicted. Besides, a huge number of rules have to be obtained. This is sometimes impractical in the real world. See a paper by A. K. C. Wong and Y. Wang, entitled “High order pattern discovery from discrete-valued data,” IEEE Trans. On Knowledge and Data Engineering, 9(6):877-893, 1997. In this case, we need a scheme which can easily re-organize the represented knowledge for different goals of the system.”
Claim 14:
The system of claim 1 is taught by Wang, Lincoln
Wang teaches:
wherein the first inference rule implemented by the processing logic of the rule overlay node outputs a weight value indicative of a degree of certainty in an evaluation of the first inference rule
[Wang 0042]: “Any data event or component event can have properties or attributes such as their probabilities of occurrence [wherein the first inference rule implemented by the processing logic of the rule overlay node outputs a weight value indicative of a degree of certainty in an evaluation of the first inference rule which is also indicated to be a form of confidence later in the quote in relation to compound events] in the data domain, or more complex qualifications. For example, in mining statistically significant associations, if a compound event c passes a significant test T, c becomes a significant pattern. The elements of c are said to have a statistically significant association according to the test T or simply they are associated. In this case, the compound event might be connected to T with confidence levels and other statistical qualifications. This can be a property or attribute of the compound event”
Claim 15:
The system of claim 14 is taught by Wang, Lincoln
Wang teaches:
wherein execution of the executable inference hypergraph further determines an inference certainty indicative of a combined degree of certainty in an evaluation of one or more inference rules of the executable inference hypergraph
[Wang 0042]: “Any data event or component event can have properties or attributes such as their probabilities of occurrence in the data domain, or more complex qualifications. For example, in mining statistically significant associations, if a compound event c passes a significant test T, c becomes a significant pattern. The elements of c are said to have a statistically significant association according to the test T or simply they are associated. In this case, the compound event might be connected to T with confidence levels [wherein execution of the executable inference hypergraph further determines an inference certainty indicative of a combined degree of certainty in an evaluation of one or more inference rules of the executable inference hypergraph as compound event confidence matches the interpretation of a combined degree of certainty for an evaluation of one or more inference rules (the mapping for claim 14 would also fit under BRI as “one or more inference rules” means a confidence or probability for a rule would count)] and other statistical qualifications. This can be a property or attribute of the compound event”
Further support is given in [Wang 0062]: “In an embodiment of the present disclosure, the attribute of each vertex may be the marginal probability of the corresponding component. The attribute of each hyperedge may contain the probability of the composite (compound event), the expected probability of the composite, or the probabilities of sub-composite one order lower. All of these attributes can be used for the retrieval and/or the inference process. Therefore, in accordance with the present disclosure, hyperedges depict or represent the qualitative relations among their elementary vertices, while the attributes associated with the hyperedges and the vertices quantify or represent these relations.”
Claim 19:
A method comprising: identifying, using processing circuitry, a graph-based model comprising one or more value nodes storing one or more values; identifying, using the processing circuitry, an executable inference hypergraph representing a rule-based model, wherein the executable inference hypergraph comprises a first hyperedge associated with a first inference rule of the rule-based model and encapsulating a plurality of value nodes storing a plurality of values such that the plurality of values form a part of a set of terms used to evaluate the first inference rule, wherein the plurality of value nodes include at least one of the one or more value nodes of the graph-based model, and a rule overlay node coupled to the first hyperedge thereby forming a first executable inference rule, wherein the rule overlay node comprises processing logic operable to evaluate the first inference rule using the set of terms encapsulated by the first hyperedge; receiving, by the processing circuitry, a trigger related to a request to perform an inference using the executable inference hypergraph; and in response to the trigger being received, executing, by the processing circuitry, the executable inference hypergraph to determine an inference outcome, wherein execution of the executable inference hypergraph includes an execution of the first executable inference rule to evaluate the first inference rule using the set of terms encapsulated by the first hyperedge.
This claim is analogous to claim 1, as all of the elements of claim 19 are noted in claim 1. Claim 19 notes “identifying”, but generic recitation of identifying something is seen as taught by the elements of claim 1, for in order to utilize an element, for something such as storing, the element must be identified otherwise one would not be able to know what was being used. Thus the teachings used for claim 1 are seen as teaching the limitations of claim 19.
Claim 20:
A non-transitory computer readable medium including instructions which, when executed by processing circuitry, cause the processing circuitry to: identify a graph-based model comprising one or more value nodes storing one or more values; identify an executable inference hypergraph representing a rule-based model, wherein the executable inference hypergraph comprises a first hyperedge associated with a first inference rule of the rule-based model and encapsulating a plurality of value nodes storing a plurality of values such that the plurality of values form a part of a set of terms used to evaluate the first inference rule, wherein the plurality of value nodes include at least one of the one or more value nodes of the graph-based model, and a rule overlay node coupled to the first hyperedge thereby forming a first executable inference rule, wherein the rule overlay node comprises processing logic operable to evaluate the first inference rule using the set of terms encapsulated by the first hyperedge; receive a trigger related to a request to perform an inference using the executable inference hypergraph; and in response to the trigger being received, execute the executable inference hypergraph to determine an inference outcome, wherein execution of the executable inference hypergraph includes an execution of the first executable inference rule to evaluate the first inference rule using the set of terms encapsulated by the first hyperedge.
This claim is analogous to claim 19.
Claims 11-13, 18 are rejected under Wang, Lincoln, and Dutkowski.
Claim 11:
The system of claim 1 is taught by Wang, Lincoln
Lincoln teaches:
wherein the first executable inference rule comprises a further overlay node comprising processing logic operable to evaluate the first inference rule, wherein the overlay node is associated with a first context and the further overlay node is associated with a second context
[Lincoln 79-82]: “Conditional rules are used to express a substitution of symbols that only occurs when a condition is met. The condition can be expressed as an "if" statement. The "if" statement is evaluated first, and, if true, the rewriting rule is performed. The use of typing enhances [wherein the first executable inference rule comprises a further overlay node comprising processing logic operable to evaluate the first inference rule, wherein the overlay node is associated with a first context and the further overlay node is associated with a second context where the explanation of what typing does matches the premise of a context as the typing changes how or which rule is performed] the capacity and expressiveness of rewriting rule statements. For example, if proteins M and N are of type A, then the rewriting rule A.fwdarw.A B is evaluated as follows: given "M", the rewriting rule produces "M B"; given "N", the rewriting rule produces "N B." Thus, symbols that are declared to be of type A (or a subtype thereof), are evaluated as A by the rule.”
Other aspects of if-then, conditions, or rules are mentioned in Wang, as noted in claim 1.
One of ordinary skill in the art, prior to the effective filing date, would have been motivated to combine Wang and Lincoln. Wang and Lincoln are in the same field of endeavor of graphs or graphing systems (such as hypergraphs). One of ordinary skill in the art would have been motivated to combine Wang and Lincoln to include typing/context in order to increase capacity and expressiveness of rules ([Lincoln 79-82]: “The use of typing the capacity and expressiveness of rewriting rule statements.”).
Alternative idea for the idea of context is provided by Dutkowski for claims 11-13 in [Dutkowski 0038]: “In a preferred embodiment, a graph or a hypergraph structure can be used to integrate and represent the relations in the knowledge base. A reference is made to FIG. 3 which presents a schematic diagram of a hypergraph-structured knowledge base. Nodes in such a hypergraph may correspond to entities (100) or entity measurements (101). Edges (102) or hyperedges (103) correspond to relations or multivariate relations between entities or entity measurements. Relations may have assigned contexts [wherein the first executable inference rule comprises a further overlay node comprising processing logic operable to evaluate the first inference rule, wherein the overlay node is associated with a first context and the further overlay node is associated with a second context] (104) or additional parameters or metadata, such as relation type (105), the type of statistical test or model used to infer the relation (106), relation direction (107), or other parameters or metadata. In a preferred embodiment both entities and entity measurements can be indexed in the knowledge base providing the ability to search for either relations specific to a given entity measurement or all relations with a given entity, irrespective of the measurement. In some embodiments entity measurements may be hierarchically organized and entity measurements from multiple or all levels of the hierarchy may be indexed, providing the ability to represent and search for hierarchically-organized entities or entity measurements and their relations.”
One of ordinary skill in the art, prior to the effective filing date, would have been motivated to combine Wang and Dutkowski. Wang and Dutkowski are in the same field of endeavor of graphs or graphing systems (such as hypergraphs). One of ordinary skill in the art would have been motivated to combine Wang and Dutkowski to include context in order to have more detail for understanding the relation or improve the ability to search through hypergraphs ([Dutkowski 0038]: “Relations may have assigned contexts (104) or additional parameters or metadata, such as relation type (105), the type of statistical test or model used to infer the relation (106), relation direction (107), or other parameters or metadata. In a preferred embodiment both entities and entity measurements can be indexed in the knowledge base providing the ability to search for either relations specific to a given entity measurement or all relations with a given entity, irrespective of the measurement. In some embodiments entity measurements may be hierarchically organized and entity measurements from multiple or all levels of the hierarchy may be indexed, providing the ability to represent and search for hierarchically-organized entities or entity measurements and their relations.”).
Claim 12:
The system of claim 11 is taught by Wang, Lincoln, Dutkowski
Lincoln teaches:
wherein the executable inference hypergraph is executed according to a received context such that the first executable inference rule is executed based on the received context
[Lincoln 79-82]: “Conditional rules are used to express a substitution of symbols that only occurs when a condition is met. The condition can be expressed as an "if" statement. The "if" statement is evaluated first, and, if true, the rewriting rule is performed. The use of typing enhances [wherein the executable inference hypergraph is executed according to a received context such that the first executable inference rule is executed based on the received context where the explanation of what typing does matches the premise of a context as the typing changes how or which rule is performed] the capacity and expressiveness of rewriting rule statements. For example, if proteins M and N are of type A, then the rewriting rule A.fwdarw.A B is evaluated as follows: given "M", the rewriting rule produces "M B"; given "N", the rewriting rule produces "N B." Thus, symbols that are declared to be of type A (or a subtype thereof), are evaluated as A by the rule.”
Other aspects of if-then, conditions, or rules are mentioned in Wang, as noted in claim 1.
The motivation to combine with Lincoln is the same as claim 11.
Alternative teaching for context is noted in claim 11 from Dutkowski.
Claim 13:
The system of claim 12 is taught by Wang, Lincoln, Dutkowski
Lincoln teaches:
wherein the overlay node is executed when the first context matches the received context and the further overlay node is executed when the second context matches the received context
[Lincoln 79-82]: “Conditional rules are used to express a substitution of symbols that only occurs when a condition is met. The condition can be expressed as an "if" statement. The "if" statement is evaluated first, and, if true, the rewriting rule is performed. The use of typing enhances [wherein the overlay node is executed when the first context matches the received context and the further overlay node is executed when the second context matches the received context where the explanation of what typing does matches the premise of a context as the typing changes how or which rule is performed] the capacity and expressiveness of rewriting rule statements. For example, if proteins M and N are of type A, then the rewriting rule A.fwdarw.A B is evaluated as follows: given "M", the rewriting rule produces "M B"; given "N", the rewriting rule produces "N B." Thus, symbols that are declared to be of type A (or a subtype thereof), are evaluated as A by the rule.”
Other aspects of if-then, conditions, or rules are mentioned in Wang, as noted in claim 1.
The motivation to combine with Lincoln is the same as claim 11.
Alternative teaching for context is noted in claim 11 from Dutkowski.
Claim 18:
The system of claim 1 is taught by Wang, Lincoln
Wang teaches:
wherein the memory further stores an inference hypergraph template from which the executable inference hypergraph is generated
[Wang 0036]: “In an embodiment according to the present disclosure, data relationships may be stored as attributed hypergraphs [wherein the memory further stores an inference hypergraph template from which the executable inference hypergraph is generated] in a computer or computer network, ready for querying and further analysis. Such a representation is simple yet general enough to directly encode association patterns of different orders discovered from data source, large databases or raw data relations with arbitrary properties. Both the qualitative (if A and B are related) and quantitative relations (A and B are related 95% of the time) are represented as attributed hyperedges. Such representation is not only lucid and transparent for visualization, but also can be used for manipulating and retrieving.”
Further support in [Wang 0037]: “The representation method according to an embodiment of the present disclosure supports ad hoc and complex associative queries while requiring no physical pre-design or restructuring. Thus, a computer storage and retrieving system (e.g., a database) can be easily implemented to store and manipulate huge amount of relations in AHG form. This is particularly important and useful for statistical patterns from machine and human generated data sources including but not limited to social media, manufacturing, and scientific research.”
An alternative teaching is noted in Figure 2 of Dutkowski (which is highlighted to help indicate relevant areas), which notes ontologies [wherein the memory further stores an inference hypergraph template from which the executable inference hypergraph is generated] and the storage of annotated variations of the ontologies (indicated the premise of having a storage of ontologies is known and the use of stored ontologies is known where an ontology is seen as a template in this case).
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One of ordinary skill in the art, prior to the effective filing date, would have been motivated to combine Wang and Dutkowski. Wang and Dutkowski are in the same field of endeavor of graphs or graphing systems (such as hypergraphs). One of ordinary skill in the art would have been motivated to combine Wang and Dutkowski to include ontology storage in order to be able to utilize the ontology as a template for another graph ([Indicated in Figure 2 of Dutkowski by the accessing and annotating of elements from the ontology]).
Claims 16 are rejected under Wang, Lincoln, and Rowe.
Claim 16:
The system of claim 14 is taught by Wang, Lincoln
Wang does not explicitly teach:
wherein the processing circuitry is configured as part of execution of the executable inference hypergraph to: compare the weight value to a threshold certainty value; when the weight value does not satisfy the threshold certainty value, obtain an additional term such that the first inference rule is re-evaluated using the set of terms and the additional term
Rowe teaches:
[Rowe 0085]: “In one or more embodiments, the action taken by the system may depend on the combination of (a) the predicted label, and (b) the confidence score associated with the predicted label. For example, if the machine learning model predicts, based a data point of a set of input data, a system failure, but if the system has a low level of confidence in the prediction (such as below 50%), the system may take an action to obtain further data [wherein the processing circuitry is configured as part of execution of the executable inference hypergraph to: compare the weight value to a threshold certainty value; when the weight value does not satisfy the threshold certainty value, obtain an additional term such that the first inference rule is re-evaluated using the set of terms and the additional term] to increase the confidence score. For example, the system may identify one or more additional sensors or data sources that may combined with the previously-obtained input data to result in a prediction having a confidence score of 70% or greater.”
Additional support is given in [Rowe 0082]: “When the system determines that the confidence score does not meet the threshold, the system may refrain from performing a system operation based on the predicted label associated with the data point (Operation 312). For example, if the machine learning model predicts failure of a particular application, and the confidence score for the prediction is less than 70%, failing to meet a threshold for the application, the system may refrain from automatically saving application data, assigning additional resources to the application, or identify other operations or applications that may cause the application to fail. Alternatively, the system may refrain from performing automatic operations to adjust currently-running applications, but the system may generate a user prompt including the prediction and the confidence score associated with the prediction. The user prompt may include one or more recommended courses of action.”
One of ordinary skill in the art, prior to the effective filing date, would have been motivated to combine Wang and Rowe. Wang and Rowe are in the same field of endeavor of machine learning. The teachings of Wang are indicate to have relation to machine learning ([Wang 0018]: “The present invention, with its generality, versatility, efficiency and flexibility, is well suited for storing and retrieving large quantity of data relationship artifacts. The invention supports data analysis and modeling naturally. Applications are evident in data and knowledge management, data mining, statistical modeling, machine learning, and other fields where data analysis is required.”). The relation to machine learning is also seen as relevant as the current application notes elements that overlap in the field of machine learning (such as classification, fault diagnosis, or autonomous vehicle control), thus one of ordinary skill in the art would aware of the practices ([Current Specification 0143]: “To help illustrate the above concepts, the description will now turn to an example application of an inference hypergraph to medical image analysis and classification. The skilled person will appreciate that the present disclosure is not intended to be limited by such an application. Indeed, the systems and methods of the present disclosure are applicable to a range of different application areas and domains such as performing inference for rule-based and explainable fault diagnosis, system control (e.g., reactor control), autonomous vehicle control, safety critical systems, and the like.”). One of ordinary skill in the art would have been motivated to combine Wang and Rowe in order to utilize threshold of confidence to re-evaluate with an additional term in order to improve confidence in prediction ([Rowe 0085]: “For example, if the machine learning model predicts, based a data point of a set of input data, a system failure, but if the system has a low level of confidence in the prediction (such as below 50%), the system may take an action to obtain further data to increase the confidence score.”).
Claims 17 are rejected under Wang, Lincoln, Rowe, and Qi.
Claim 17:
The system of claim 16 is taught by Wang, Lincoln, Rowe
Wang does not explicitly teach:
wherein the additional term is obtained from a user of the system
Qi teaches:
[Qi 0102]: “For example, for a particular crash event, the second machine-learning model may generate a second confidence in which the value of the airbag deployment data type is set to non-deployment (e.g., airbag did not deploy). It may be determined that the second confidence is less than a threshold value confidence. The second machine-learning model may generate an additional second confidence in which the value of the airbag deployment data type indicates deployed. It may be determined that the additional second confidence is greater than the threshold value confidence. Since there is a conflict (e.g., a difference) between the second confidence and the additional second confidence that would change the output (e.g., whether a total loss is identified), the total loss module determines that the airbag deployment information may be necessary to determine if the crash event is a total loss event. In those instances, a request for additional information via a user input [wherein the additional term is obtained from a user of the system] may be requested to obtain the airbag information. In some cases, the second machine-learning model may compute a threshold difference between the second confidence and the additional second confidence to determine that a conflict is present (e.g., a 20% difference).”
One of ordinary skill in the art, prior to the effective filing date, would have been motivated to combine Wang and Qi. Wang and Qi are in the same field of endeavor of machine learning. The connection to machine learning for Wang and the current application are noted in claim 16 for the motivation to combine with Rowe. One of ordinary skill in the art would have been motivated to combine Wang and Qi in order to include using user input as an additional item as low confidence or conflicting confidence requires additional input to determine a proper answer (). The combination with Rowe in claim 16 notes additional term teachings and also Rowe teaches user input in paragraph 45 of specification, thus the combination of Qi on top of Rowe is a sensible combination to note the additional term could be given by the user is obvious, for Rowe already teaches the elements and Qi is showing the combination of user input as an additional term is already known.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Evans et al (US 20220121939) is relevant art, for Evans discusses hypergraphs, such as creating or training hypergraphs.
Quamar et al (US 20210103586 A1) is relevant art that discusses ontology based query routing that utilizes hypergraphs, thus shows relevant teachings for ontologies/templates for hypergraphs as well as aspects related to the creation of hypergraphs.
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/C.D.D./Examiner, Art Unit 2129
/MICHAEL J HUNTLEY/Supervisory Patent Examiner, Art Unit 2129
