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(s) 1, 2, 4, 6-9, 11, 13-16, 18, and 20 are pending for examination. Claim(s) 1, 8, 14, and 15 are amended. Claim(s) 3, 5, 10, 12, 17, and 19 are cancelled. This action is Final.
Response to Arguments
Applicant's arguments filed 1/21/2026 with respect to the 35 U.S.C. 101 rejection have been fully considered but they are not persuasive.
Applicant Argues: Applicant respectfully disagrees with the Examiner's contentions, and humbly submits that amended claims 1, 2, 4, 6-9, 11, 13-16, 18 and 20 are directed to patent eligible subject matter at least for the reasons below. For ease of the Examiner's reference, the Applicant followed the 2019 Revised Patent Subject Matter Eligibility Guidance by USPTO released on Jan 4, 2019. The Applicant humbly requests the Examiner to consider the claims under revised guidelines, when identifying a concept as a judicial exception.
Examiner’s Response: The examiner respectfully disagrees for the reasons set forth below.
Re: Step 2A- Prong 2: Claims recite a method for Multi-level reliability assessment of vendors based on multi-dimensional reliability score thereby integrate the exception into practical application based on combination of additional elements.
Applicant Argues: Applicant asserts that integration of judicial exception into the practical application is achieved in terms of an improvement to computing technology and/or improving the functionality of the computer (MPEP §§ 2106.04(d)(1) and 2106.05(a)), with the capability of understanding the requirement of the entity or organization in finding a right vendor for right purpose from among a plurality of vendors already involved with the entity's one or other part of supply chain of a plurality of supply items. The requirements can vary with focus of the entity on different levels at which a vendor has to be identified and not necessarily always at organizational level. Thus, vendor information both from internal information available with the entity and external information sourced from various resources has to be gathered and analyzed. The vendor data, specifically the internal data needs to be cleansed and validated in accordance with input data requirement of each of the plurality scores computations. This is performed using standard data cleaning procedures using PYTHON™ and SQL™ queries. Data Validation check is done for date range, null records and PO item combinations for a given category to obtain clean data without null records, duplicate records, column names in the output mapped to corresponding standard column names and so on. The amended of claim 1 recites "determining via the one or more hardware processors, vendor-to-item mapping information, vendor-to-item category mapping information and vendor to department mapping information for each of the plurality of vendors for each of the plurality of items in each of the plurality of categories by processing the vendor data post performing data validation, wherein the data validation checks for date range, null records and PO item combinations for a category to obtain a clean data without null records, duplicate records, column names in an output mapped to corresponding standard column names;"
Examiner’s Response: The examiner respectfully disagrees. The examiner respectfully notes as argued (i.e., with the capability of understanding the requirement of the entity or organization in finding a right vendor for right purpose from among a plurality of vendors already involved with the entity's one or other part of supply chain of a plurality of supply item), and similarly claimed, “...determining... vendor-to-item mapping information, vendor-to-item category mapping information and vendor to department mapping information for each of the plurality of vendors for each of the plurality of items in each of the plurality of categories by processing the vendor data post performing data validation, wherein the data validation checks for date range, null records and PO item combinations for a category to obtain a clean data without null records, duplicate records, column names in an output mapped to corresponding standard column names” are noted to be part of the abstract idea, thus the purported improvement, lies within the abstract idea itself.
The features of “...“...determining... vendor-to-item mapping information, vendor-to-item category mapping information and vendor to department mapping information for each of the plurality of vendors for each of the plurality of items in each of the plurality of categories by processing the vendor data post performing data validation, wherein the data validation checks for date range, null records and PO item combinations for a category to obtain a clean data without null records, duplicate records, column names in an output mapped to corresponding standard column names” are noted to fall within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas as they recite business relations.
The examiner further respectfully notes use of “a hardware processor” to “determine” is noted to be additional elements are described at a high level in Applicant’s specification without any meaningful detail about their structure or configuration. These elements in the steps are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using a generic computer component and merely invoke such additional elements as a tool to perform the abstract idea. See MPEP 2106.05(f). Further, by applicant’s own admission such “cleansing”/“validation “techniques are standard data cleaning producers. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea. Therefore, this argument is not persuasive.
Applicant Argues: Applicant asserts that integration of judicial exception into the practical application is achieved in terms of an improvement to computing technology and/or improving the functionality of the computer (MPEP §§ 2106.04(d)(1) and 2106.05(a)), with the capability of providing a holistic multi-dimensional reliability score that aggregates multiple, multi- dimensional scores for a supplier, generated at item, item category, department and organizational level using internal and external vendor data. More specifically, the claimed subject matter enables segregation of supplier performance evaluation into multiple sections, multifactor individual score calculation using sophisticated and statistical and Machine Learning (ML) algorithms to further aggregate individual scores to generate the multi-dimensional reliability score. The approach provided herein facilitates objectivity, flexibility, and completeness to the vendor assessment, with customization in reliability score assessment as, "computing via the one or more hardware processors, a plurality of scores for each of the plurality of vendors by processing the vendor-to-item mapping information, the vendor-to-category mapping information, and the vendor to department mapping information, wherein the plurality of scores are generated at a plurality of levels comprising an item level, an item category level, a department level and an entity level, the plurality of scores comprising: “computing via the one or more hardware processors a plurality of scores... a) popularity score... b) pricing score... c) timeliness score... d) sustainability score... e) financial score... f) compliance score... and g) market score...;”
Examiner’s Response: The examiner respectfully disagrees. The examiner respectfully notes as argued (i.e., with the capability of providing a holistic multi-dimensional reliability score that aggregates multiple, multi- dimensional scores for a supplier, generated at item, item category, department and organizational level using internal and external vendor data), and similarly claimed, “...computing ... a plurality of scores... a) popularity score... b) pricing score... c) timeliness score... d) sustainability score... e) financial score... f) compliance score... and g) market score...” are noted to be part of the abstract idea, thus the purported improvement, lies within the abstract idea itself.
The features of “...computing ... a plurality of scores... a) popularity score... b) pricing score... c) timeliness score... d) sustainability score... e) financial score... f) compliance score... and g) market score...” are noted to fall within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas as they recite business relations.
The examiner further respectfully notes use of “a hardware processor” to “compute” is noted to be additional elements are described at a high level in Applicant’s specification without any meaningful detail about their structure or configuration. These elements in the steps are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using a generic computer component and merely invoke such additional elements as a tool to perform the abstract idea. See MPEP 2106.05(f). The examiner acknowledges the use of a TS model trained, however, such features are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using a generic computer component and merely invoke such additional elements as a tool to perform the abstract idea Further, it is noted that the features upon which applicant relies (i.e., using sophisticated and statistical and Machine Learning (ML,) algorithms) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea. Therefore, this argument is not persuasive.
Applicant Argues: Applicant asserts that integration of judicial exception into the practical application is achieved in terms of an improvement to computing technology and/or improving the functionality of the computer (MPEP §§ 2106.04(d)(1) and 2106.05(a)), with the capability of selecting vendors among multiple vendors for an item of interest based on a reliability score criteria. The reliability criteria can be predefined to select and display top 3 vendors based on highest scores, and the final selection can be left to SME or the end user. The amended of claim 1 recites "selecting via the one or more hardware processors, one or more vendors from the plurality of vendors for an item of interest based on a reliability score criteria in accordance with a level of interest from among the item level, the item-category level, the department level, and the organizational level, wherein the reliability score criteria is predefined to select and display top vendors based on highest scores for selecting the one or more vendors by a user.”
Examiner’s Response: The examiner respectfully disagrees. The examiner respectfully notes as argued, and similarly claimed, “selecting ...one or more vendors from the plurality of vendors for an item of interest based on a reliability score criteria in accordance with a level of interest from among the item level, the item-category level, the department level, and the organizational level, wherein the reliability score criteria is predefined to select and display top vendors based on highest scores for selecting the one or more vendors by a user” are noted to be part of the abstract idea, thus the purported improvement, lies within the abstract idea itself.
The features of “selecting ...one or more vendors from the plurality of vendors for an item of interest based on a reliability score criteria in accordance with a level of interest from among the item level, the item-category level, the department level, and the organizational level, wherein the reliability score criteria is predefined to select and display top vendors based on highest scores for selecting the one or more vendors by a user” are noted to fall within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas as they recite business relations.
The examiner further respectfully notes use of “a hardware processor” to “select” is noted to be additional elements are described at a high level in Applicant’s specification without any meaningful detail about their structure or configuration. These elements in the steps are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using a generic computer component and merely invoke such additional elements as a tool to perform the abstract idea. See MPEP 2106.05(f). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea. Therefore, this argument is not persuasive.
Applicant Argues: The Applicant ascertains that the method disclosed herein provides a holistic multi dimensional reliability score that aggregates multiple, multi-dimensional scores for a supplier, generated at item, item category, department and organizational level using internal and external vendor data. These scores uncover hidden patterns present in various aspects of transaction of a supplier with the organization as well as external aspects of a supplier such as financial health, environmental impact and market sentiment related to the supplier. The reliability score can be customized by assigning varying weights to individual scores based on one or more dimensions the user is focused on during vendor selection.
...
Therefore, the ordered combination of claimed elements integrates the exception into practical application.
Thus, the claim is eligible because it is not directed to the recited judicial exception (abstract idea) under Step 2A-Prong 2 of the revised guidance for assessing the Patent Subject Mater Eligibility.
The Applicant requests the Examiner to consider the above-mentioned arguments and submissions on merits. Further, based on the 2019 Revised Patent Subject Mater Eligibility Guidance, it is to be noted that Step 2A-Prong 2 does not evaluate whether the additional elements are conventional to determine whether the abstract idea is integrated into a practical application.
Examiner’s Response: The examiner respectfully disagrees. The examiner notes that the argued concept of “a holistic multi dimensional reliability score that aggregates multiple, multi-dimensional scores for a supplier, generated at item, item category, department and organizational level using internal and external vendor data. These scores uncover hidden patterns present in various aspects of transaction of a supplier with the organization as well as external aspects of a supplier such as financial health, environmental impact and market sentiment related to the supplier. The reliability score can be customized by assigning varying weights to individual scores based on one or more dimensions the user is focused on during vendor selection” which is paraphrased language of the claim limitations as noted below in the rejection are noted to be part of the abstract idea, thus the purported improvement, lies within the abstract idea itself. Additionally, Claim 1, and for similar claim(s) 8 and 15, recite i.e., one or more processors, including trained models and/or storage in a database, and memory, input/output interfaces, storage mediums w/ instructions. These additional elements are described at a high level in Applicant’s specification without any meaningful detail about their structure or configuration. These elements in the steps are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using a generic computer component and merely invoke such additional elements as a tool to perform the abstract idea. See MPEP 2106.05(f). Accordingly, these additional elements, even in combination, do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea. Therefore, this argument is not persuasive.
Step 2B: Claims recite additional element(s) that amount to significantly more than the judicial exception(s).
Applicant Argues: In addition to the claim limitations satisfying Step 2A Prong 2 test criteria, the Applicant respectfully submits that claimed elements/limitations recites patent eligible subject matter.
...
Applicant submits that the present invention describes computing a plurality of scores for each of the plurality of vendors by processing the vendor-to-item mapping information, the vendor-to-category mapping information, and the vendor to department mapping information. In the claimed subject matter, the plurality of scores are generated at a plurality of levels such as an item level, an item, category level, a department level, and an entity level. Moreover, the mapping information being used for computing the plurality of scores such as the vendor-to-item mapping information, the vendor-to-category mapping information, and the vendor to department mapping information helps to identify extent of individual vendors presence in the entity's supply chain at various levels. Further, the claimed subject matter describes computing includes computing the popularity score, the pricing score, the timeliness score with help of the internal data, while the sustainability score, the financial score, the compliance score, and the market reputation score IS computed using the information from the external data.
Examiner’s Response: The examiner notes that the argued concept of “computing a plurality of scores for each of the plurality of vendors by processing the vendor-to-item mapping information, the vendor-to-category mapping information, and the vendor to department mapping information. In the claimed subject matter, the plurality of scores are generated at a plurality of levels such as an item level, an item, category level, a department level, and an entity level... the mapping information being used for computing the plurality of scores such as the vendor-to-item mapping information, the vendor-to-category mapping information, and the vendor to department mapping information helps to identify extent of individual vendors presence in the entity's supply chain at various levels... computing includes computing the popularity score, the pricing score, the timeliness score with help of the internal data, while the sustainability score, the financial score, the compliance score, and the market reputation score IS computed using the information from the external data” which is paraphrased language of the claim limitations as noted below in the rejection are noted to be part of the abstract idea, thus the purported improvement, lies within the abstract idea itself.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when considered separately and as an ordered combination, they do not add significantly more to the exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of for claim 1, and for similar claim(s) 8 and 15, i.e., one or more processors, including trained models and/or storage in a database, and memory, input/output interfaces, storage mediums w/ instruction; thus, amounts to no more than mere instructions to apply the exception using a generic computer component and do not add anything that is not already present when they are considered individually or in combination. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Therefore, this argument is not persuasive.
Applicant Argues: In accordance with a level of interest for a supplier generated at item, item category, department and organizational level and enabling segregation of supplier performance evaluation into multiple sections, multi-factor individual score calculation using sophisticated and statistical and Machine Learning (ML,) algorithms to further aggregate individual scores to generate the multi-dimensional reliability score.
Examiner’s Response: The examiner notes that the argued concept of “a level of interest for a supplier generated at item, item category, department and organizational level and enabling segregation of supplier performance evaluation into multiple sections, multi-factor individual score calculation ... to further aggregate individual scores to generate the multi-dimensional reliability score” which is paraphrased language of the claim limitations as noted below in the rejection are noted to be part of the abstract idea, thus the purported improvement, lies within the abstract idea itself.
The examiner acknowledges the use of a TS model that has been trained, however, such features are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using a generic computer component and merely invoke such additional elements as a tool to perform the abstract idea and further is only used for predicting a timeliness score. Further, it is noted that the features upon which applicant relies (i.e., using sophisticated and statistical and Machine Learning (ML) algorithms) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims.
Thus, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when considered separately and as an ordered combination, they do not add significantly more to the exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of for claim 1, and for similar claim(s) 8 and 15, i.e., one or more processors, including trained models and/or storage in a database, and memory, input/output interfaces, storage mediums w/ instruction; thus, amounts to no more than mere instructions to apply the exception using a generic computer component and do not add anything that is not already present when they are considered individually or in combination. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Therefore, this argument is not persuasive.
Applicant Argues: Accordingly, the claimed subject matter provides a solution to bring a paradigm-shift from using rules or an isolated machine learning algorithms to score supplier risk to a holistic reliability score which aggregates multiple, multi-dimensional scores for a supplier generated at item, item category, department & organizational level using internal and external data. For instance, in the claimed subject matter, the internal data is the organizational proprietary wherein the actual Purchase Order (PO) details are available. Further, the external data is made available from multiple data providers who analyze the vendors at global level. Internal data related to vendor details, PO delivery details, PO item details are used for developing scores like popularity score, pricing score, timeliness score. However, to generate sustainability score, financial score, compliance score and market reputation score different sets of external data are required. These scores are aggregated to derive an overall multi-dimensional reliability score for the vendor or supplier.
Moreover, in the claimed subject matter, the feature group level scores generated for each of the item-vendor combinations undergo dynamic curve fitting using an activation function enabling effective and justified discrimination between the feature group level scores. This curve fitting is performed for effective and justified discrimination between the scores. The application of activation function enables transformed output distribution of scores upon passing through the required activation function.
Examiner’s Response: The examiner notes that the argued concept of “to score supplier risk to a holistic reliability score which aggregates multiple, multi-dimensional scores for a supplier generated at item, item category, department & organizational level using internal and external data.” Further as argued “...the internal data is the organizational proprietary wherein the actual Purchase Order (PO) details are available... the external data is made available from multiple data providers who analyze the vendors at global level... Internal data related to vendor details, PO delivery details, PO item details are used for developing scores like popularity score, pricing score, timeliness score... generate sustainability score, financial score, compliance score and market reputation score different sets of external data are required.... These scores are aggregated to derive an overall multi-dimensional reliability score for the vendor or supplier” and which is paraphrased language of the claim limitations as noted below in the rejection are noted to be part of the abstract idea, thus the purported improvement, lies within the abstract idea itself.
The examiner acknowledges the use of a TS model that has been trained, however, such features are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using a generic computer component and merely invoke such additional elements as a tool to perform the abstract idea and further is only used for predicting a timeliness score. Further, it is noted that the features upon which applicant relies (i.e., using sophisticated and statistical and Machine Learning (ML) algorithms and “the feature group level scores generated for each of the item-vendor combinations undergo dynamic curve fitting using an activation function enabling effective and justified discrimination between the feature group level scores. This curve fitting is performed for effective and justified discrimination between the scores. The application of activation function enables transformed output distribution of scores upon passing through the required activation function”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims.
Thus, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when considered separately and as an ordered combination, they do not add significantly more to the exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of for claim 1, and for similar claim(s) 8 and 15, i.e., one or more processors, including trained models and/or storage in a database, and memory, input/output interfaces, storage mediums w/ instruction; thus, amounts to no more than mere instructions to apply the exception using a generic computer component and do not add anything that is not already present when they are considered individually or in combination. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Therefore, this argument is not persuasive.
Applicant Argues: In the claimed subject matter, the TS Model or ML model is built using the timeliness features and uses a XGBoost model trained on all the features data for the historically closed POs. The XGBoost or Extreme Gradient Boosting, is a scalable, distributed gradient-boosted decision tree (GBDT) machine learning library. It provides parallel tree boosting and is the leading machine learning library for regression, classification, and ranking problems. Further, the market reputation score is derived from a sentiment score calculated from marker news information, obtained from the external data, using Natural Language Processing (NLP) and indicates the level of sentiment shared by reviewers for that vendor. Similarly, the plurality of scores calculated for various dimensions, each focusing on different dimension or aspect associated with vendor.
Examiner’s Response: The examiner respectfully notes limitations that are not indicative of integration into a practical application include: adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (MPEP 2106.05(f)), Claim 1, and for similar claim(s) 8 and 15, recite i.e., trained model. This additional elements are described at a high level in Applicant’s specification without any meaningful detail about their structure or configuration (see Applicant’s Specification, ⁋⁋ [0029]-[0034]). The TS model trained via Extreme Gradient Boost/XG Boost is an element in the steps that is recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using a generic computer component and merely invoke such additional element as a tool to perform the abstract idea. See MPEP 2106.05(f). Accordingly, these additional elements, even in combination, do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea. Further, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when considered separately and as an ordered combination, they do not add significantly more to the exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of for claim 1, and for similar claim(s) 8 and 15, i.e., trained models, amounts to no more than mere instructions to apply the exception using a generic computer component and do not add anything that is not already present when they are considered individually or in combination. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Therefore, this argument is not persuasive.
Applicant Argues: The method disclosed herein provides a holistic multi dimensional reliability score that aggregates multiple, multi-dimensional scores for a supplier, generated at item, item category, department and organizational level using internal and external vendor data. These scores uncover hidden patterns present in various aspects of transaction of a supplier with the organization as well as external aspects of a supplier such as financial health, environmental impact and marketsentiment related to the supplier. The reliability score can be customized by assigning varying weights to individual scores based on one or more dimensions the user is focused on during vendor selection.
Therefore, Applicant submits that the claimed subject matter provides a multi- dimensionality reliability score that is aggregated version of all the different scores to provide a holistic amalgamated view of a vendor/supplier competitiveness and sustainability, and this contributes to a technical problem. More specifically, the claimed subject matter provides a solution to a technical problem on how to evaluate and establish a robust assurance mechanism which cover supplier risks related to: visibility of supplier networks; financial, ethical, social, and environment performance; need for assurance around legal and statutory compliance, and confidence in handling supply chain disruption. Moreover these scores uncover hidden patterns present in various aspects of transaction of a supplier with the organization as well as external aspects of a supplier such as financial health, environmental impact and market sentiment related to the supplier.
Examiner’s Response: The examiner respectfully disagrees. The examiner notes that the argued concept of “a holistic multi dimensional reliability score that aggregates multiple, multi-dimensional scores for a supplier, generated at item, item category, department and organizational level using internal and external vendor data. These scores uncover hidden patterns present in various aspects of transaction of a supplier with the organization as well as external aspects of a supplier such as financial health, environmental impact and market sentiment related to the supplier. The reliability score can be customized by assigning varying weights to individual scores based on one or more dimensions the user is focused on during vendor selection” which is paraphrased language of the claim limitations as noted below in the rejection are noted to be part of the abstract idea, thus the purported improvement, lies within the abstract idea itself.
The provided “multi- dimensionality reliability score that is aggregated version of all the different scores to provide a holistic amalgamated view of a vendor/supplier competitiveness and sustainability” is part of the of the abstract idea and does not "purport(s) to improve the functioning of the computer itself" or "any other technology or technical field." The claimed language invokes computers merely as a tool and/or does not improve technology beyond the computer functionality. Therefore, this argument is not persuasive.
Applicant Argues: Applicant's claimed invention recites the technical advancement in terms of:
1. Building a layer of intelligence that transforms multi-dimensional data to generate Pricing, Popularity and Timeliness scores using purchase order transactions. The data contains relationships between supplier, category and item combinations which if ignored will result in discrepancy in scoring,
2. Identification of multiple factors for each score to ensure that each individual score sufficiently represents supplier performance in that area,
3. Use of score calculation mechanism using both statistical and machine learning models,
4. Blending scores like Popularity Score, Pricing Score, Timeliness Score, Sustainability score, Financial Score, Compliance Score and Market Reputation Score by implementing a custom method that uses dynamic weights defined by a user to create a reliability score. Hence, the presently amended claims amount to significantly more than the abstract idea.
Examiner’s Response: The provided “...transforms multi-dimensional data to generate Pricing, Popularity and Timeliness scores using purchase order transactions. The data contains relationships between supplier, category and item combinations which if ignored will result in discrepancy in scoring”, “Identification of multiple factors for each score to ensure that each individual score sufficiently represents supplier performance in that area”, “calculation mechanisms” and “Blending scores like Popularity Score, Pricing Score, Timeliness Score, Sustainability score, Financial Score, Compliance Score and Market Reputation Score by implementing a custom method that uses dynamic weights defined by a user to create a reliability score” is part of the abstract idea and does not "purport(s) to improve the functioning of the computer itself" or "any other technology or technical field." The claimed language invokes computers merely as a tool and/or does not improve technology beyond the computer functionality.
Further, it is noted that the features upon which applicant relies (i.e., using sophisticated and statistical and Machine Learning (ML) algorithms) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims.
Thus, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when considered separately and as an ordered combination, they do not add significantly more to the exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of for claim 1, and for similar claim(s) 8 and 15, i.e., one or more processors, including trained models and/or storage in a database, and memory, input/output interfaces, storage mediums w/ instruction; thus, amounts to no more than mere instructions to apply the exception using a generic computer component and do not add anything that is not already present when they are considered individually or in combination. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Therefore, this argument is not persuasive
Applicant Argues: In view of the foregoing, the Applicant asserts that the Applicant claimed subject matter provides for multi-level reliability assessment of vendors based on multi dimensional reliability score by performing data analytics on vendor data. The method disclosed herein bring a paradigm-shift from using rules or an isolated machine learning algorithms to score supplier risk to a holistic reliability score which aggregates multiple, multi-dimensional scores for a supplier generated at item, item category, department and organizational level using internal and external vendor data (refer paragraphs [025, 048, 062, 068, 077]).
Therefore, taking all the claim elements individually, or in combination, the claim as a whole amounts to "significantly more" than an abstract idea of itself (Step 2B: Yes).
The Applicant requests the examiner to consider the above-mentioned arguments and submissions on merits. By means of the aforementioned claim amendments and submissions, Applicant humbly and respectfully submits that the subject matter claimed does not merely constitute an abstract idea and constitutes significantly more than an abstract idea.
Accordingly, the Applicant respectfully requests the withdrawal of the rejection of claims 1, 2, 4, 6-9, 11, 13-16, 18 and 20 under 35 U.S.C § 101.
Examiner’s Response: The examiner respectfully disagrees for the reasons previously argued above (i.e., in summation).
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.
Claim(s) 1-2,4,6-9,11,13-16,18 and 20 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract idea without significantly more.
Step 1: claim(s) 1-20 are directed to a machine, process, and/or manufacture. Therefore, the claims are directed to statutory subject matter under Step 1 (Step 1: YES). See MPEP 2106.03.
Prong 1, Step 2A: claim 1, and similar claim(s) 8 and 15, taken as representative, recites at least the following limitations that recite an abstract idea:
A
obtaining
determining
computing
a) a popularity score (POPS), indicative of a weighted combination of metrics representing popularity of a vendor in terms of a plurality of popularity features based on share of business, total volume of materials supplied, and frequency of supply, which is extracted from the internal data, wherein each of the plurality of popularity features is determined over varying time periods and uniquely combined to form a plurality of popularity features groups (FGs), wherein the plurality of popularity FGs are dynamically created based on item-vendor combinations, duration for which the internal data and the external data is available, and an user configuration setting defining the varying time periods for each of the plurality of popularity feature groups, wherein a feature group level score is generated for each of the item-vendor combinations and combined to obtain the popularity score, wherein feature group level scores generated for each of the item-vendor combinations undergo dynamic curve fitting using an activation function enabling effective and justified discrimination between the feature group level scores, wherein the activation function is selected from among a plurality of activation functions based on a measure of kurtosis associated with each of the plurality of activation functions and for all the activation functions, the kurtosis is calculated and the activation function with least kurtosis is selected as a final activation function to calculate POPS for all the aggregation levels including item, item code, departments;
b) a pricing score (PRS), indicative of the comparative price charged by a vendor from among the plurality of vendors for an item with respect to other vendors based on a plurality of pricing features comprising (i) mean price, highest price, and lowest price of each of the plurality of vendors, (ii) volume of items supplied by each of the plurality of vendors, and (iii) total volume of items supplied by the plurality of vendors, wherein the pricing features are extracted from the internal data;
c) a timeliness score (TS) predicted by a Timeline Score (TS) model trained on a plurality of timeliness features extracted from the internal data and comprising a historical performance of a vendor and other vendors for a single item and across the plurality of items, across the plurality of levels, wherein the TS is used to predict whether a particular vendor deliver a product or an item within an expected duration or delay the delivery, and wherein the TS Model is an Extreme Gradient Boosting, XGBoost
d) a sustainability score (SS) obtained by integrating a plurality of sustainability sub-scores obtained for each of the plurality of vendors from the external data, wherein the SS is mapped for corresponding vendors using supplier ID and
e) a financial score (FS) obtained by integrating a plurality of financial parameter scores assigned to each of the plurality of vendors, extracted from the external data;
f) a compliance score (CS) by integrating a plurality of compliance parameter scores assigned to each of the plurality of vendor, extracted from the external data; and
g) a market reputation score (MRS) derived from a sentiment score calculated from marker news information, obtained from the external data, using Natural Language Processing (NLP), wherein the MRS indicates a level of sentiment shared by reviews for a particular vendor;
normalizing
dynamically assigning weightage
assessing
selecting via the one or more hardware processors, one or more vendors from the plurality of vendors for an item of interest based on a reliability score criteria in accordance with a level of interest from among the item level, the item-category level, the department level, and the organizational level, wherein the reliability score criteria is predefined to select and display top vendors based on highest scores for selecting the one or more vendors by a user.
The above limitations, under their broadest reasonable interpretation, fall within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas, enumerated in MPEP 2106.04(a)(2)(II), in that they recite "commercial interactions" or "legal interactions" include agreements in the form of contracts, legal obligations, advertising, marketing or sales activities or behaviors, and business relations. The broadest reasonable interpretation of these limitations for claim 1, and for similar claim(s) 8 and 15 includes obtaining vendor data...; determining vendor-to-item mapping information, vendor-to-item category mapping information and vendor to department mapping...; computing a plurality of scores for each of the plurality of vendors by processing the vendor- to-item mapping information, the vendor-to-category mapping information, and the vendor to department mapping information, wherein the plurality of scores are generated at a plurality of levels comprising an item level, an item category level, a department level and an entity level, the plurality of scores comprising: a) a popularity score (POPS)... b) a pricing score (PRS)... c) a timeliness score (TS)...; d) a sustainability score (SS)...;
e) a financial score (FS)...; f) a compliance score (CS)...; and g) a market reputation score (MRS)...; normalizing... the plurality of scores on a predefined scale; dynamically assigning weightage to each of the normalized plurality of scores...; assessing ... each of the plurality of vendors by determining a multi-dimensional reliability score for each of the plurality of vendors at each of the plurality of levels by aggregating the plurality of weighted scores; and selecting ...one or more vendors from the plurality of vendors for an item of interest based on a reliability score criteria in accordance with a level of interest from among the item level, the item-category level, the department level, and the organizational level, thus, claim 1 similar claim(s) 8 and 15, falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas as they recite “commercial interactions" or "legal interactions" in the form of business relations.
Accordingly, these claims recite an abstract idea. (Prong 1, Step 2A: YES). The types of identified abstract ideas are considered together as a single abstract idea for analysis purposes.
Prong 2, Step 2A: Limitations that are not indicative of integration into a practical application include: (1) Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (MPEP 2106.05(f)), (2) Adding insignificant extra-solution activity to the judicial exception (MPEP 2106.05(g)), (3) Generally linking the use of the judicial exception to a particular technological environment or field of use (MPEP 2106.05(h)). Claim 1, and for similar claim(s) 8 and 15, recite i.e., one or more processors, including trained models and/or storage in a database, and memory, input/output interfaces, storage mediums w/ instructions. These additional elements are described at a high level in Applicant’s specification without any meaningful detail about their structure or configuration (see Applicant’s Specification, ⁋⁋ [0029]-[0034]). These elements in the steps are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using a generic computer component and merely invoke such additional elements as a tool to perform the abstract idea. See MPEP 2106.05(f). Accordingly, these additional elements, even in combination, do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
As such, under Prong 2 of Step 2A, when considered both individually and as a whole, the limitations of claim 1, and for similar claim(s) 8 and 15 are not indicative of integration into a practical application (Prong 2, Step 2A: NO). See MPEP 2106.04(d).
Since claim 1, and similar claim(s) 8 and 15 recites an abstract idea and fails to integrate the abstract idea into a practical application, claim 1, and similar claim(s) 8 and 15 is “directed to” an abstract idea under Step 2A (Step 2A: YES). See MPEP 2106.04(d).
Step 2B: The recitation of the additional elements is acknowledged, as identified above with respect to Prong 2 of Step 2A. These additional elements do not add significantly more to the abstract idea for the same reasons as addressed above with respect to Prong 2 of Step 2A.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when considered separately and as an ordered combination, they do not add significantly more to the exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of for claim 1, and for similar claim(s) 8 and 15, i.e., one or more processors, including trained models and/or storage in a database, and memory, input/output interfaces, storage mediums w/ instruction; thus, amounts to no more than mere instructions to apply the exception using a generic computer component and do not add anything that is not already present when they are considered individually or in combination. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Therefore, under Step 2B, there are no meaningful limitations in claim 1, and similar claim(s) 8 and 15 that transform the judicial exception into a patent eligible application such that the claims amount to significantly more than the judicial exception itself (Step 2B: NO). See MPEP 2106.05.
Accordingly, under the Subject Matter Eligibility test, claim 1, and similar claim(s) 8 and 15 is ineligible.
Regarding Claims 2, 4, 6-7, 11, 13-14, 18 and 20, claims 2, 4, 6-7, 11, 13-14, 18 and 20 further defines the abstract idea that is present in their respective independent claims and hence are abstract for at least the reasons presented above w/ respect to “Certain Methods of Organizing Human Activity” as the claims recite further concepts of "commercial interactions" or "legal interactions" include agreements in the form of contracts, legal obligations, advertising, marketing or sales activities or behaviors, and business relations i.e., further features related to reliability assessment. These dependent claim does not include any additional elements that integrate the abstract idea into a practical application; as such elements are recited at a high level of generality such that it amounts not more than mere instructions to apply the exception using a generic computer component. Even in combination, these additional elements do not integrate the abstract idea into a practical application and do no not amount to significantly more than the abstract idea itself. Thus, the aforementioned claims are not patent-eligible.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/ASFAND M SHEIKH/Primary Examiner, Art Unit 3626