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 .
Detailed Action
This action is in response to the claims filed 1/8/2024:
Claims 1 – 20 are pending.
Claims 1, 8, and 14 are independent.
Claim Rejections - 35 USC § 112
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 9-13 and 15-20 are 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.
Regarding claims 9, 11-13, 15-18, and 20, "claim Error! Reference source not found" replaces the expected claim number in the text. The claims do not identify preceding claims making the scope of the claim unclear.
Claims 10 and 19 are rejected with respect to their dependence on rejected claims 9 and 18.
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claims 9-13 and 15-20 are rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends.
Regarding claims 9, 11-13, 15-18, and 20, "claim Error! Reference source not found" replaces the expected claim number in the text.
Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements.
Claims 10 and 19 are rejected with respect to their dependence on rejected claims 9 and 18.
Claim Rejections - 35 USC § 101
101 Rejection
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 1-14 are rejected under 35 USC § 101 because the claimed invention is directed to non-statutory subject matter.
Regarding Claim 1: Claim 1 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 1 is directed to a system, which is directed to a product, one of the statutory categories.
Step 2A Prong One Analysis: Claim 1 under its broadest reasonable interpretation is a series of mental processes. For example, but for the generic computer components language, the above limitations in the context of this claim encompass machine learning processing, including the following:
enforcing data quality with machine learning (observation, evaluation, and judgement)
apply the proposed rule to the set of structured data (observation, evaluation, and judgement)
Therefore, claim 1 recites an abstract idea which is a judicial exception.
Step 2A Prong Two Analysis: Claim 1 recites additional elements “one or more memories; and one or more processors, communicatively coupled to the one or more memories, configured to”. However, these additional features are computer components recited at a high-level of generality, such that they amount to no more than mere instructions to apply the judicial exception using a generic computer component. An additional element that merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, does not integrate the judicial exception into a practical application (See MPEP 2106.05(f)). Claim 1 also recites additional elements “receive, from at least one data source, a set of structured data;”, “provide the set of structured data to a machine learning model to receive an indication of a proposed rule;”, “transmit, to an administrator device, a prompt indicating the proposed rule;”, “receive, from the administrator device and in response to the prompt, an acceptance of the proposed rule;”, and “transmit, to a ticket system, a command to open at least one ticket associated with an outcome of applying the proposed rule to the set of structured data.” which amounts to gathering and outputting data which is insignificant extra-solution activity (See MPEP 2106.05(g)). Therefore, claim 1 is directed to a judicial exception.
Step 2B Analysis: Claim 1 does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the lack of integration of the abstract idea into a practical application, the additional elements recited in claim 1 amount to no more than mere instructions to apply the judicial exception using a generic computer component and insignificant extra-solution activity. The gathering and outputting of data is considered well-understood, routine, and conventional in the art (See MPEP 2106.05(d)(II)(i)).
For the reasons above, claim 1 is rejected as being directed to non-patentable subject matter under §101. This rejection applies equally to dependent claims 2-7. The additional limitations of the dependent claims are addressed briefly below:
Dependent claim 2 recites additional observation, evaluation, and judgement “wherein the proposed rule comprises at least one regular expression”
Dependent claim 3 recites additional insignificant extra-solution activity of gathering and outputting data (See MPEP 2106.05(g)) “wherein the one or more processors, to transmit the prompt, are configured to: transmit instructions for a user interface (UI) that indicates the proposed rule” which is well-understood, routine, and conventional in the art (see MPEP 2106.05(d)(II)(i))
Dependent claim 4 recites additional insignificant extra-solution activity of gathering and outputting data (See MPEP 2106.05(g)) “to receive the acceptance, are configured to: receive an indication of an interaction with a confirmation element in the UI, wherein the acceptance comprises the indication of the interaction.” which is well-understood, routine, and conventional in the art (see MPEP 2106.05(d)(II)(i))
Dependent claim 5 recites additional observation, evaluation, and judgement “to apply the proposed rule, are configured to: determine a compliance indicator associated with the set of structured data, wherein the outcome comprises the compliance indicator”
Dependent claim 6 recites additional observation, evaluation, and judgement “to apply the proposed rule, are configured to: filter out a portion of the set of structured data, wherein the outcome comprises an indication of the portion of the set of structured data”
Dependent claim 7 recites additional observation, evaluation, and judgement “the machine learning model is disallowed from modifying the set of structured data”
Regarding Claim 8: Claim 8 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 8 is directed to a method, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: Claim 8 under its broadest reasonable interpretation is a series of mental processes. For example, but for the generic computer components language, the above limitations in the context of this claim encompass machine learning processing, including the following:
enforcing data quality with machine learning (observation, evaluation, and judgement)
applying, by the analysis system, the proposed rule to the set of structured data (observation, evaluation, and judgement)
Therefore, claim 8 recites an abstract idea which is a judicial exception.
Step 2A Prong Two Analysis: Claim 8 recites additional elements “one or more memories; and one or more processors, communicatively coupled to the one or more memories, configured to”. However, these additional features are computer components recited at a high-level of generality, such that they amount to no more than mere instructions to apply the judicial exception using a generic computer component. An additional element that merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, does not integrate the judicial exception into a practical application (See MPEP 2106.05(f)). Claim 8 also recites additional elements “receiving, at an analysis system and from at least one data source, a set of structured data;”, “providing, by the analysis system, the set of structured data to a machine learning model to receive an indication of a proposed rule;”, “transmitting, from the analysis system and to an administrator device, a prompt indicating the proposed rule;”, “receiving, at the analysis system and from the administrator device, an acceptance of the proposed rule in response to the prompt;”, and “transmitting, from the analysis system and to the administrator device, an indication of an outcome of applying the proposed rule to the set of structured data.” which amounts to gathering and outputting data which is insignificant extra-solution activity (See MPEP 2106.05(g)). Therefore, claim 8 is directed to a judicial exception.
Step 2B Analysis: Claim 8 does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the lack of integration of the abstract idea into a practical application, the additional elements recited in claim 8 amount to no more than mere instructions to apply the judicial exception using a generic computer component and insignificant extra-solution activity. The gathering and outputting of data is considered well-understood, routine, and conventional in the art (See MPEP 2106.05(d)(II)(i)).
For the reasons above, claim 8 is rejected as being directed to non-patentable subject matter under §101. This rejection applies equally to dependent claims 9-13. The additional limitations of the dependent claims are addressed briefly below:
Dependent claim 9 recites additional insignificant extra-solution activity of gathering and outputting data (See MPEP 2106.05(g)) “transmitting, to the at least one data source, at least one request for the set of structured data, wherein the set of structured data is received in response to the at least one request” which is well-understood, routine, and conventional in the art (See MPEP 2106.05(d)(II)(i))
Dependent claim 10 recites additional insignificant extra-solution activity of gathering and outputting data (See MPEP 2106.05(g)) “receiving, at the analysis system, a set of credentials associated with the at least one data source, wherein the at least one request includes the set of credentials” which is well-understood, routine, and conventional in the art (see MPEP 2106.05(d)(II)(i))
Dependent claim 11 recites additional insignificant extra-solution activity of gathering and outputting data (See MPEP 2106.05(g)) “transmitting the indication of the outcome of applying the proposed rule comprises: transmitting an email message including the indication of the outcome.” which is well-understood, routine, and conventional in the art (see MPEP 2106.05(d)(II)(i))
Dependent claim 12 recites additional insignificant extra-solution activity of gathering and outputting data (See MPEP 2106.05(g)) “providing the set of structured data to the machine learning model comprises: transmitting, to a machine learning host, the set of structured data; and receiving, from the machine learning host and in response to transmitting the set of structured data, the indication of the proposed rule.” which is well-understood, routine, and conventional in the art (see MPEP 2106.05(d)(II)(i))
Dependent claim 13 recites additional observation, evaluation, and judgement “the machine learning model is disallowed from modifying the set of structured data”
Therefore, when considering the elements separately and in combination, they do not add significantly more to the inventive concept. Accordingly, claims 1-14 are rejected under 35 U.S.C. § 101.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1 and 3-20 are rejected under U.S.C. §102(a)(1) as being anticipated by Udapa (US 20230039338 A1).
Regarding claim 1, Udapa teaches A system for enforcing data quality with machine learning, the system comprising:([¶0005] "the disclosed systems utilize a specially trained machine-learning model to generate an emerging user segment based on a target outcome for digital survey responses and respondent attributes of respondents to such digital surveys." [¶0053] "the environment 100 may include one or more analytics databases storing survey response data, anonymized (e.g., scrubbed) data, etc" processing raw external data interpreted as enforcing data quality)
one or more memories; and one or more processors, communicatively coupled to the one or more memories, configured to:([¶0145] "The computing device 800 includes memory 804, which is coupled to the processor(s) 802. The memory 804 may be used for storing data, metadata, and programs for execution by the processor(s). ")
receive, from at least one data source, a set of structured data;([¶0046] "the server(s) 102 receive, in response to a digital survey, survey responses from the respondent client devices 107 a-107 n" [¶0051] "the third-party server(s) 110 host a storage database for storing digital content (e.g., survey responses, machine-learning models)" [¶0061] "the emerging user segment system 104 uses a schematization mapping" [¶0041] "the term “schematization mapping” refers to a data structure for aligning fields. In particular embodiments, a digital mapping can include a data structure for storing mapping pairs or field assignments that relate a survey field to a repository field. For example, a digital mapping may include mapping pairs arranged in an index, vector, table, nodal graph, data tree, etc" [¶0042] "a field can include a cell, row, column, box, or line (e.g., in a digital survey, database, array, storage repository, or user interface)" schematization mapping interpreted as an example of structured data)
provide the set of structured data to a machine learning model to receive an indication of a proposed rule; ([¶0126] "utilizing a machine-learning model, an emerging user segment" [¶0058] "the machine-learning model 212 generates the emerging user segment 215 by analyzing the respondent attributes 208" [¶0034] "a target outcome includes criteria for identifying a subset of respondents to a digital survey" Emerging user segment in Udapa is a classification defined by attributes and target outcome criteria, where the emerging user segment is interpreted as a proposed rule.)
transmit, to an administrator device, a prompt indicating the proposed rule; ([¶0047] "the emerging user segment system 104 provides a segment visualization of the emerging user segment for display within a graphical user interface of a client device, such as the administrator client device 106.")
receive, from the administrator device and in response to the prompt, an acceptance of the proposed rule;([¶0019] "the emerging user segment system surfaces an intuitive segment visualization for display that includes graphics, plain text description, statistical indicators, and/or a selectable option to add the emerging user segment." [¶0128] "providing, for display within the graphical user interface, an adding option to add the emerging user segment to a user account and a discard option to reject the emerging user segment for the user account; and based on receiving an indication of a user interaction with the adding option" the administrator client device selecting the segment to add it is interpreted as receiving an acceptance of the proposed rule in response to the prompt)
apply the proposed rule to the set of structured data; and([¶0092] "Subsequently, the emerging user segment system 104 can generate the predicted emerging user segment 406 that corresponds to the threshold sentiment score by identifying and grouping users from the users 401 that correspond to the predicted combination(s) of respondent attributes." [¶0059] "the emerging user segment system 104 excludes from the emerging user segment 215 users for each of the client devices 202" [¶0103] "update segment characteristics of the emerging user segment, or generate a digital ticket" Udapa applies the segment criteria to survey data by identifying users that satisfy the criteria, grouping them into the segment, and excluding users that do not match. After acceptance, Udapa saves the segment for subsequent tracking and can dynamically update segment characteristics)
transmit, to a ticket system, a command to open at least one ticket associated with an outcome of applying the proposed rule to the set of structured data. ([¶0026] "the emerging user segment system can perform one or more digital actions for the emerging user segment" [¶0043] "a digital action can include transmitting an electronic communication, generating a digital survey, updating segment characteristics of an emerging user segment, or generating a digital ticket" [¶0107] "the emerging user segment system 104 performs a digital action 510 by generating a digital ticket based on the emerging user segment 215 [...] the emerging user segment system 104 autogenerates and transmits the digital ticket to the assigned client device(s) and/or an administrator device").
Regarding claim 3, Udapa teaches The system of claim 1, wherein the one or more processors, to transmit the prompt, are configured to: transmit instructions for a user interface (UI) that indicates the proposed rule. (Udapa [¶0019] "the emerging user segment system surfaces an intuitive segment visualization for display that includes graphics, plain text description, statistical indicators, and/or a selectable option to add the emerging user segment." [¶0128] "providing, for display within the graphical user interface, an adding option to add the emerging user segment to a user account and a discard option to reject the emerging user segment for the user account; and based on receiving an indication of a user interaction with the adding option" the administrator client device selecting the segment to add it is interpreted as receiving an acceptance of the proposed rule in response to the prompt).
Regarding claim 4, Udapa teaches The system of claim 3, wherein the one or more processors, to receive the acceptance, are configured to: receive an indication of an interaction with a confirmation element in the UI, wherein the acceptance comprises the indication of the interaction. (Udapa [¶0019] "the emerging user segment system surfaces an intuitive segment visualization for display that includes graphics, plain text description, statistical indicators, and/or a selectable option to add the emerging user segment." [¶0128] "providing, for display within the graphical user interface, an adding option to add the emerging user segment to a user account and a discard option to reject the emerging user segment for the user account; and based on receiving an indication of a user interaction with the adding option" the administrator client device selecting the segment to add it is interpreted as receiving an acceptance of the proposed rule in response to the prompt).
Regarding claim 5, Udapa teaches The system of claim 1, wherein the one or more processors, to apply the proposed rule, are configured to: determine a compliance indicator associated with the set of structured data, wherein the outcome comprises the compliance indicator. (Udapa [¶0125] " selecting the subset of survey responses comprises selecting survey responses that satisfy both the target outcome and at least one respondent attribute." [¶0068] "the emerging user segment system 104 neural network can determine or identify respondent attributes for respondents with classification scores or confidence levels that satisfy a deterministic threshold." [¶0071] ", the emerging user segment system 104 may detect that the user input provides a range of customer satisfaction scores, user-exit-threshold probabilities (e.g., churn probabilities), etc" Udapa uses threshold satisfaction, confidence scores, error probably, and other efficacy metrics as compliance indicators).
Regarding claim 6, Udapa teaches The system of claim 1, wherein the one or more processors, to apply the proposed rule, are configured to: filter out a portion of the set of structured data,(Udapa [¶0023] "the emerging user segment system filters the survey responses based on one or more of the target outcome or the respondent attributes to identify a subset of survey responses. […] the emerging user segment system selects only the survey responses corresponding to the respondent attributes and/or the target outcome.")
wherein the outcome comprises an indication of the portion of the set of structured data. (Udapa [¶0120] "the computing device 600 presents the individual users that comprise the emerging user segment for display within the user interface 602").
Regarding claim 7, Udapa teaches The system of claim 1, wherein the machine learning model is disallowed from modifying the set of structured data. (Udapa [Abstract] "utilize a specially trained machine-learning model to generate an emerging user segment based on a target outcome for digital survey responses and respondent attributes of respondents to such digital surveys" The machine learning model in Udapa never modifies the original structured dataset).
Regarding claim 8, Udapa teaches A method of enforcing data quality with machine learning, comprising:([¶0005] "the disclosed systems utilize a specially trained machine-learning model to generate an emerging user segment based on a target outcome for digital survey responses and respondent attributes of respondents to such digital surveys." [¶0053] "the environment 100 may include one or more analytics databases storing survey response data, anonymized (e.g., scrubbed) data, etc" processing raw external data interpreted as enforcing data quality)
receiving, at an analysis system and from at least one data source, a set of structured data;([¶0046] "the server(s) 102 receive, in response to a digital survey, survey responses from the respondent client devices 107 a-107 n" [¶0051] "the third-party server(s) 110 host a storage database for storing digital content (e.g., survey responses, machine-learning models)" [¶0061] "the emerging user segment system 104 uses a schematization mapping" [¶0041] "the term “schematization mapping” refers to a data structure for aligning fields. In particular embodiments, a digital mapping can include a data structure for storing mapping pairs or field assignments that relate a survey field to a repository field. For example, a digital mapping may include mapping pairs arranged in an index, vector, table, nodal graph, data tree, etc" schematization mapping interpreted as an example of structured data)
providing, by the analysis system, the set of structured data to a machine learning model to receive an indication of a proposed rule;([¶0126] "utilizing a machine-learning model, an emerging user segment" [¶0058] "the machine-learning model 212 generates the emerging user segment 215 by analyzing the respondent attributes 208" [¶0034] "a target outcome includes criteria for identifying a subset of respondents to a digital survey" Emerging user segment in Udapa is a classification defined by attributes and target outcome criteria, where the emerging user segment is interpreted as a proposed rule.)
transmitting, from the analysis system and to an administrator device, a prompt indicating the proposed rule;([¶0047] "the emerging user segment system 104 provides a segment visualization of the emerging user segment for display within a graphical user interface of a client device, such as the administrator client device 106.")
receiving, at the analysis system and from the administrator device, an acceptance of the proposed rule in response to the prompt;([¶0019] "the emerging user segment system surfaces an intuitive segment visualization for display that includes graphics, plain text description, statistical indicators, and/or a selectable option to add the emerging user segment." [¶0128] "providing, for display within the graphical user interface, an adding option to add the emerging user segment to a user account and a discard option to reject the emerging user segment for the user account; and based on receiving an indication of a user interaction with the adding option" the administrator client device selecting the segment to add it is interpreted as receiving an acceptance of the proposed rule in response to the prompt)
applying, by the analysis system, the proposed rule to the set of structured data; and ([¶0092] "Subsequently, the emerging user segment system 104 can generate the predicted emerging user segment 406 that corresponds to the threshold sentiment score by identifying and grouping users from the users 401 that correspond to the predicted combination(s) of respondent attributes." [¶0059] "the emerging user segment system 104 excludes from the emerging user segment 215 users for each of the client devices 202" [¶0103] "update segment characteristics of the emerging user segment, or generate a digital ticket" Udapa applies the segment criteria to survey data by identifying users that satisfy the criteria, grouping them into the segment, and excluding users that do not match. After acceptance, Udapa saves the segment for subsequent tracking and can dynamically update segment characteristics)
transmitting, from the analysis system and to the administrator device, an indication of an outcome of applying the proposed rule to the set of structured data. ([¶0026] "the emerging user segment system can perform one or more digital actions for the emerging user segment" [¶0043] "a digital action can include transmitting an electronic communication, generating a digital survey, updating segment characteristics of an emerging user segment, or generating a digital ticket" [¶0107] "the emerging user segment system 104 performs a digital action 510 by generating a digital ticket based on the emerging user segment 215 [...] the emerging user segment system 104 autogenerates and transmits the digital ticket to the assigned client device(s) and/or an administrator device").
Regarding claim 9, Udapa teaches The method of claim Error! Reference source not found., further comprising: transmitting, to the at least one data source, at least one request for the set of structured data,(Udapa [¶0046] "the server(s) 102 receive, in response to a digital survey, survey responses from the respondent client devices 107 a-107 n" [¶0051] "the third-party server(s) 110 host a storage database for storing digital content (e.g., survey responses, machine-learning models)" [¶0061] "the emerging user segment system 104 uses a schematization mapping" [¶0041] "the term “schematization mapping” refers to a data structure for aligning fields. In particular embodiments, a digital mapping can include a data structure for storing mapping pairs or field assignments that relate a survey field to a repository field. For example, a digital mapping may include mapping pairs arranged in an index, vector, table, nodal graph, data tree, etc" [¶0129] " identifying candidate respondent attributes from a schematization mapping that maps survey response data to predefined fields" schematization mapping interpreted as an example of structured data)
wherein the set of structured data is received in response to the at least one request. (Udapa [¶0046] "the server(s) 102 receive, in response to a digital survey, survey responses from the respondent client devices 107 a-107 n" [¶0051] "the third-party server(s) 110 host a storage database for storing digital content (e.g., survey responses" [¶0042] "a field can include a cell, row, column, box, or line (e.g., in a digital survey, database, array, storage repository, or user interface)" Udapa explicitly states that the servers receive survey responses in response to a digital survey. The received responses are structured in a map having cells, rows, columns, boxes, or lines).
Regarding claim 10, Udapa teaches The method of claim 9, further comprising: receiving, at the analysis system, a set of credentials associated with the at least one data source, wherein the at least one request includes the set of credentials. (Udapa [¶0082] "the emerging user segment system 104 can identify the subset of users by locating each client device identifier, user account identifier, etc. associated with non-respondents that have one or more of the attributes that are the same as or that correspond to the subset of the respondent attributes 208" user account identifier interpreted as credentials associated with the at least one data source).
Regarding claim 11, Udapa teaches The method of claim Error! Reference source not found., wherein transmitting the indication of the outcome of applying the proposed rule comprises: transmitting an email message including the indication of the outcome. (Udapa [¶0104] "To illustrate the digital action 504, the emerging user segment system 104 can transmit, to a client device, an electronic communication comprising one or more of an SMS message, instant message, e-mail, social media post, etc").
Regarding claim 12, Udapa teaches The method of claim Error! Reference source not found., wherein providing the set of structured data to the machine learning model comprises: transmitting, to a machine learning host, the set of structured data; and(Udapa [¶0046] "the server(s) 102 receive, in response to a digital survey, survey responses from the respondent client devices 107 a-107 n" [¶0051] "the third-party server(s) 110 host a storage database for storing digital content (e.g., survey responses, machine-learning models)" [¶0061] "the emerging user segment system 104 uses a schematization mapping" [¶0041] "the term “schematization mapping” refers to a data structure for aligning fields. In particular embodiments, a digital mapping can include a data structure for storing mapping pairs or field assignments that relate a survey field to a repository field. For example, a digital mapping may include mapping pairs arranged in an index, vector, table, nodal graph, data tree, etc" [¶0129] " identifying candidate respondent attributes from a schematization mapping that maps survey response data to predefined fields" schematization mapping interpreted as an example of structured data)
receiving, from the machine learning host and in response to transmitting the set of structured data, the indication of the proposed rule. (Udapa [¶0047] "Subsequently, in one or more embodiments, the emerging user segment system 104 generates, utilizing a machine-learning model, an emerging user segment based on the target outcome, the respondent attributes, and the subset of survey responses. Additionally, the emerging user segment system 104 provides a segment visualization of the emerging user segment for display within a graphical user interface of a client device, such as the administrator client device 106." [¶0060] "The segment visualization can include one or more visual aids for representing and/or recommending the emerging user segment 215" Udapa explicitly discloses that the machine learning model generates an emerging user segment from the input data and that the system provides a visualization representing that segment).
Regarding claim 13, Udapa teaches The method of claim Error! Reference source not found., wherein the machine learning model is disallowed from modifying the set of structured data. (Udapa [Abstract] "utilize a specially trained machine-learning model to generate an emerging user segment based on a target outcome for digital survey responses and respondent attributes of respondents to such digital surveys" The machine learning model in Udapa never modifies the original structured dataset).
Regarding claim 14, Udapa teaches A non-transitory computer-readable medium storing a set of instructions for enforcing data quality with machine learning, the set of instructions comprising:([¶0005] "the disclosed systems utilize a specially trained machine-learning model to generate an emerging user segment based on a target outcome for digital survey responses and respondent attributes of respondents to such digital surveys." [¶0053] "the environment 100 may include one or more analytics databases storing survey response data, anonymized (e.g., scrubbed) data, etc" processing raw external data interpreted as enforcing data quality)
one or more instructions that, when executed by one or more processors of a device, cause the device to:([¶0145] "The computing device 800 includes memory 804, which is coupled to the processor(s) 802. The memory 804 may be used for storing data, metadata, and programs for execution by the processor(s). ")
transmit a command to assess a set of structured data;([¶0046] "the server(s) 102 receive, in response to a digital survey, survey responses from the respondent client devices 107 a-107 n" [¶0051] "the third-party server(s) 110 host a storage database for storing digital content (e.g., survey responses, machine-learning models)" [¶0061] "the emerging user segment system 104 uses a schematization mapping" [¶0041] "the term “schematization mapping” refers to a data structure for aligning fields. In particular embodiments, a digital mapping can include a data structure for storing mapping pairs or field assignments that relate a survey field to a repository field. For example, a digital mapping may include mapping pairs arranged in an index, vector, table, nodal graph, data tree, etc" [¶0042] "a field can include a cell, row, column, box, or line (e.g., in a digital survey, database, array, storage repository, or user interface)" schematization mapping interpreted as an example of structured data)
receive, in response to the command, an indication of a proposed rule to apply to the set of structured data, wherein the proposed rule is from a machine learning model;([¶0126] "utilizing a machine-learning model, an emerging user segment" [¶0058] "the machine-learning model 212 generates the emerging user segment 215 by analyzing the respondent attributes 208" [¶0034] "a target outcome includes criteria for identifying a subset of respondents to a digital survey" Emerging user segment in Udapa is a classification defined by attributes and target outcome criteria, where the emerging user segment is interpreted as a proposed rule.)
transmit, based on input from a user of the device, an acceptance of the proposed rule; and([¶0047] "the emerging user segment system 104 provides a segment visualization of the emerging user segment for display within a graphical user interface of a client device, such as the administrator client device 106.")
receive, in response to the acceptance, an indication of an outcome of applying the proposed rule to the set of structured data. ([¶0019] "the emerging user segment system surfaces an intuitive segment visualization for display that includes graphics, plain text description, statistical indicators, and/or a selectable option to add the emerging user segment." [¶0128] "providing, for display within the graphical user interface, an adding option to add the emerging user segment to a user account and a discard option to reject the emerging user segment for the user account; and based on receiving an indication of a user interaction with the adding option" the administrator client device selecting the segment to add it is interpreted as receiving an acceptance of the proposed rule in response to the prompt).
Regarding claim 15, Udapa teaches The non-transitory computer-readable medium of claim Error! Reference source not found., wherein the one or more instructions, when executed by the one or more processors, cause the device to: transmit a set of credentials associated with at least one data source that stores the set of structured data. (Udapa [¶0082] "the emerging user segment system 104 can identify the subset of users by locating each client device identifier, user account identifier, etc. associated with non-respondents that have one or more of the attributes that are the same as or that correspond to the subset of the respondent attributes 208" user account identifier interpreted as credentials associated with the at least one data source).
Regarding claim 16, Udapa teaches The non-transitory computer-readable medium of claim Error! Reference source not found., wherein the one or more instructions, that cause the device to receive the indication of the outcome, cause the device to: receive a compliance indicator associated with the set of structured data. (Udapa [¶0125] " selecting the subset of survey responses comprises selecting survey responses that satisfy both the target outcome and at least one respondent attribute." [¶0068] "the emerging user segment system 104 neural network can determine or identify respondent attributes for respondents with classification scores or confidence levels that satisfy a deterministic threshold." [¶0071] ", the emerging user segment system 104 may detect that the user input provides a range of customer satisfaction scores, user-exit-threshold probabilities (e.g., churn probabilities), etc" Udapa uses threshold satisfaction, confidence scores, error probably, and other efficacy metrics as compliance indicators).
Regarding claim 17, Udapa teaches The non-transitory computer-readable medium of claim Error! Reference source not found., wherein the one or more instructions, that cause the device to receive the indication of the outcome, cause the device to: receive an indication of a portion, of the set of structured data, that was filtered out. (Udapa [¶0023] "the emerging user segment system filters the survey responses based on one or more of the target outcome or the respondent attributes to identify a subset of survey responses. […] the emerging user segment system selects only the survey responses corresponding to the respondent attributes and/or the target outcome.").
Regarding claim 18, Udapa teaches The non-transitory computer-readable medium of claim Error! Reference source not found., wherein the one or more instructions, that cause the device to receive the indication of the proposed rule, cause the device to: receive instructions for a user interface (UI) that indicates the proposed rule. (Udapa [¶0019] "the emerging user segment system surfaces an intuitive segment visualization for display that includes graphics, plain text description, statistical indicators, and/or a selectable option to add the emerging user segment." [¶0128] "providing, for display within the graphical user interface, an adding option to add the emerging user segment to a user account and a discard option to reject the emerging user segment for the user account; and based on receiving an indication of a user interaction with the adding option" the administrator client device selecting the segment to add it is interpreted as receiving an acceptance of the proposed rule in response to the prompt).
Regarding claim 19, Udapa teaches The non-transitory computer-readable medium of claim 18, wherein the one or more instructions, that cause the device to transmit the acceptance, cause the device to: transmit an indication of an interaction with a confirmation element in the UI,(Udapa [¶0019] "the emerging user segment system surfaces an intuitive segment visualization for display that includes graphics, plain text description, statistical indicators, and/or a selectable option to add the emerging user segment." [¶0128] "providing, for display within the graphical user interface, an adding option to add the emerging user segment to a user account and a discard option to reject the emerging user segment for the user account; and based on receiving an indication of a user interaction with the adding option" the administrator client device selecting the segment to add it is interpreted as receiving an acceptance of the proposed rule in response to the prompt)
wherein the acceptance comprises the indication of the interaction. (Udapa [¶0092] "Subsequently, the emerging user segment system 104 can generate the predicted emerging user segment 406 that corresponds to the threshold sentiment score by identifying and grouping users from the users 401 that correspond to the predicted combination(s) of respondent attributes." [¶0059] "the emerging user segment system 104 excludes from the emerging user segment 215 users for each of the client devices 202" [¶0103] "update segment characteristics of the emerging user segment, or generate a digital ticket" Udapa applies the segment criteria to survey data by identifying users that satisfy the criteria, grouping them into the segment, and excluding users that do not match. After acceptance, Udapa saves the segment for subsequent tracking and can dynamically update segment characteristics).
Regarding claim 20, Udapa teaches The non-transitory computer-readable medium of claim Error! Reference source not found., wherein the one or more instructions, when executed by the one or more processors, cause the device to: receive an indication of an additional proposed rule to apply to the set of structured data;(Udapa [¶0126] "utilizing a machine-learning model, an emerging user segment" [¶0058] "the machine-learning model 212 generates the emerging user segment 215 by analyzing the respondent attributes 208" [¶0034] "a target outcome includes criteria for identifying a subset of respondents to a digital survey" [¶0087] "the emerging user segment system 104 can intelligently identify or predict emerging user segments based on target outcomes and corresponding respondent attributes. FIG. 4A illustrates the emerging user segment system 104 training an emerging-user-segment-machine-learning model 404 to generate predicted emerging user segments" Emerging user segments in Udapa are a classification defined by attributes and target outcome criteria, where the emerging user segment is interpreted as a proposed rule. Udapa explicitly anticipates a plurality of emerging user segments.)
transmit, based on additional input from the user of the device, a rejection of the additional proposed rule; and(Udapa [¶0047] "the emerging user segment system 104 provides a segment visualization of the emerging user segment for display within a graphical user interface of a client device, such as the administrator client device 106.")
receive, in response to the rejection, an indication that the additional proposed rule was discarded. (Udapa [¶0019] "the emerging user segment system surfaces an intuitive segment visualization for display that includes graphics, plain text description, statistical indicators, and/or a selectable option to add the emerging user segment." [¶0128] "providing, for display within the graphical user interface, an adding option to add the emerging user segment to a user account and a discard option to reject the emerging user segment for the user account; and based on receiving an indication of a user interaction with the adding option" the administrator client device selecting the segment to add it is interpreted as receiving an acceptance of the proposed rule in response to the prompt).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
Claim 2 is rejected under U.S.C. §103 as being unpatentable over the combination of Udapa and Nelke (US20120158625A1).
Regarding claim 2, Udapa teaches The system of claim 1.
However, Udapa doesn't explicitly teach, wherein the proposed rule comprises at least one regular expression.
Nelke, in the same field of endeavor, teaches the proposed rule comprises at least one regular expression. ([¶0005] "A further rule may be defined to verify that the values in the column always match a regular expression").
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Martin (US20220276920A1) is directed towards rule based data quality correction using machine learning.
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/SIDNEY VINCENT BOSTWICK/Examiner, Art Unit 2124
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