DETAILED ACTION
Acknowledgements
The amendment filed on 07/17/2025 is acknowledged.
Claims 1-21 are pending.
Claims 1-21 have been examined.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment/Arguments
Claims 1, 14 and19 are amended.
Regarding applicant’s arguments on Claim Rejections - 35 U.S.C. §101, the arguments have been fully considered but they are not persuasive.
It is the applicant’s position that “The claims are patent eligible at least under Step 2A, Prong Two because the claims are directed to a practical application of technology.” The Examiner respectfully disagrees.
The claim(s) recite(s) managing user identity based user’s transaction data. Specifically, the claims recite “establishing an identity graph including a plurality of user clusters, each user cluster being associated with a different user and including one or more user profile nodes, each user profile node being associated with a customer account of a user, such that each of the one or more user profile nodes within a cluster correspond to different customer accounts of the user, wherein a customer account comprises a plurality of identifying attributes of the user and each user profile node corresponds to a different manner in which the user interacts with a retail enterprise; obtaining transaction data associated with an account used in a transaction…; identifying one or more nodes within the identity graph that correspond to one of a plurality of possible identity matches by performing a ... matching process between the transaction data and the one or more nodes, wherein the ... matching process identifies a correspondence between identifying attributes included in the transaction data with identifying attributes of customer accounts associated with the respective one or more nodes; for each of the one or more nodes, providing the transaction data and an identification of the node … to obtain a determination of whether the transaction data is associated with the node based on a selected threshold probability score, the [classifier model] being trained using training transaction data linked to the customer accounts corresponding to user profile nodes in the identity graph, wherein the probability score represents an extent of similarity between the transaction data and the node; and based on a determination… that the transaction data is associated with a node of the one or more nodes, establishing an identity edge between the node and a user profile node corresponding to the account, thereby adding the user profile node corresponding to the account to a cluster that includes the node.”, which is “managing personal behavior or relationships or interactions between people” within the “certain methods of organizing human activity” grouping of abstract ideas in prong one of step 2A of the Alice/Mayo test (See MPEP 2106) because the claims involve a series of steps for processing transaction request. Accordingly, the claims recite an abstract idea.
Additionally, the claims recite graph theory “establishing an identity graph including a plurality of user clusters, each user cluster being associated with a different user and including one or more user profile nodes, each user profile node being associated with a customer account of a user, such that each of the one or more user profile nodes within a cluster correspond to different customer accounts of the user, wherein a customer account comprises a plurality of identifying attributes of the user and each user profile node corresponds to a different manner in which the user interacts with a retail enterprise; …establishing an identity edge between the node and a user profile node corresponding to the account, thereby adding the user profile node corresponding to the account to a cluster that includes the node.” which is the abstract idea of a mathematical concept. See MPEP 2106. Therefore, the claims recite an abstract idea, as it has been held that a combination of abstract ideas, in this case certain methods of organizing human activity and a mathematical concept, is still an abstract idea. See FairWarning IP, LLC v. Iatric Sys., Inc., 839 F.3d 1089, 1093-94 (Fed. Cir. 2016).
This judicial exception is not integrated into a practical application because, when analyzed under prong two of step 2A of the Alice/Mayo test (See MPEP 2106), the additional element(s) of the claim(s) such as the use of deterministic matching, classifier model, processor, and memory merely use(s) a computer as a tool to perform an abstract idea. The processors and memories are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function of managing user relationships and identities) such that it amounts no more than mere instructions to apply the exception using a generic computer components. Accordingly, the additional elements do not impose any meaningful limits on practicing the abstract idea, and the claims are directed to an abstract idea.
The applicant argues that the judicial exception is integrated into a practical application because “claim 1 reflects an improvement to identifying and strengthening relationships between matching nodes in such a way that not only allows for improved accuracy and completeness, but also enhanced flexibility and computational efficiency.” The examiner respectfully disagrees.
Applying graph theory, deterministic and probabilistic matching to transaction data for collecting and organizing user data is a business process. It does not purport to improve the functioning of the computer itself. Nor do they effect an improvement in any other technology or technical field.
Therefore, the rejection is maintained.
Regarding applicant’s arguments on Claim Rejections - 35 U.S.C. §103, the amendments overcome the rejection. The rejection has been withdrawn.
Claim Rejections - 35 USC §101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Analysis
In the instant case, claims 1-13 are directed to a method, claims 14-18 are directed to a CRM, and claims 19-21 are directed to a system. Therefore, these claims fall within the four statutory categories of invention.
The claim(s) recite(s) managing user identity based user’s transaction data. Specifically, the claims recite “establishing an identity graph including a plurality of user clusters, each user cluster being associated with a different user and including one or more user profile nodes, each user profile node being associated with a customer account of a user, such that each of the one or more user profile nodes within a cluster correspond to different customer accounts of the user, wherein a customer account comprises a plurality of identifying attributes of the user and each user profile node corresponds to a different manner in which the user interacts with a retail enterprise; obtaining transaction data associated with an account used in a transaction…; identifying one or more nodes within the identity graph that correspond to one of a plurality of possible identity matches by performing a ... matching process between the transaction data and the one or more nodes, wherein the ... matching process identifies a correspondence between identifying attributes included in the transaction data with identifying attributes of customer accounts associated with the respective one or more nodes; for each of the one or more nodes, providing the transaction data and an identification of the node … to obtain a determination of whether the transaction data is associated with the node based on a selected threshold probability score, the [classifier model] being trained using training transaction data linked to the customer accounts corresponding to user profile nodes in the identity graph, wherein the probability score represents an extent of similarity between the transaction data and the node; and based on a determination… that the transaction data is associated with a node of the one or more nodes, establishing an identity edge between the node and a user profile node corresponding to the account, thereby adding the user profile node corresponding to the account to a cluster that includes the node.”, which is “managing personal behavior or relationships or interactions between people” within the “certain methods of organizing human activity” grouping of abstract ideas in prong one of step 2A of the Alice/Mayo test (See MPEP 2106) because the claims involve a series of steps for processing transaction request. Accordingly, the claims recite an abstract idea.
Additionally, the claims recite graph theory “establishing an identity graph including a plurality of user clusters, each user cluster being associated with a different user and including one or more user profile nodes, each user profile node being associated with a customer account of a user, such that each of the one or more user profile nodes within a cluster correspond to different customer accounts of the user, wherein a customer account comprises a plurality of identifying attributes of the user and each user profile node corresponds to a different manner in which the user interacts with a retail enterprise; …establishing an identity edge between the node and a user profile node corresponding to the account, thereby adding the user profile node corresponding to the account to a cluster that includes the node.” which is the abstract idea of a mathematical concept. See MPEP 2106. Therefore, the claims recite an abstract idea, as it has been held that a combination of abstract ideas, in this case certain methods of organizing human activity and a mathematical concept, is still an abstract idea. See FairWarning IP, LLC v. Iatric Sys., Inc., 839 F.3d 1089, 1093-94 (Fed. Cir. 2016).
This judicial exception is not integrated into a practical application because, when analyzed under prong two of step 2A of the Alice/Mayo test (See MPEP 2106), the additional element(s) of the claim(s) such as the use of deterministic matching, classifier model, processor, and memory merely use(s) a computer as a tool to perform an abstract idea. The processors and memories are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function of managing user relationships and identities) such that it amounts no more than mere instructions to apply the exception using a generic computer components. Accordingly, the additional elements do not impose any meaningful limits on practicing the abstract idea, and the claims are directed to an abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using deterministic matching, classifier model, processor, and memory steps amounts to no more than mere instructions to apply the exception using a generic computer components. Mere instructions to apply an exception using a generic computer components cannot provide an inventive concept. The claim is not patent eligible.
Dependent claims 2-3 and 5 describe user account. Dependent claims 4, 10-11 and 17-18 describe user profile node. Dependent claims 6-8 and 15-16 describe classifier model. Dependent claims 9 and 12 describe identity edge. Dependent claims 13 and 20-21 describes identity graph. This judicial exception is not integrated into a practical application because the additional element(s) of the claim(s) such as the use of deterministic matching, classifier model, processor, and memory merely use(s) a computer as a tool to perform an abstract idea. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claims are not patent eligible.
Viewed as a whole, the combination of elements recited in the claims simply recite the concept of managing user identity based user’s transaction data. The claims do not, for example, purport to improve the functioning of the computer itself. Nor do they effect an improvement in any other technology or technical field.
The use of deterministic matching, classifier model, processor, and memory as tools to implement the abstract idea does not render the claim patent eligible because it does not provide meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment and requires no more than a computer performing functions that correspond to acts required to carry out the abstract idea.
Allowable Subject Matter
Claims 1-21 would be allowable if rewritten or amended to overcome the rejection(s) under 35 U.S.C. 101 set forth in this Office action. The closest prior art of record is US20180349800A1 (“Saba et al.”). Saba et al. teaches A customer identity management platform used within a retail enterprise, the customer identity management platform comprising: (Fig. 1 item 104) a computing system comprising a memory and a processor, the memory storing instructions which, when executed by the processor, cause the computing system to: (¶0086) establish an identity graph including one or more user profile nodes, each user profile node being associated with a customer account of a customer, such that each of the one or more user profile nodes within a cluster correspond to different customer accounts of the customer; (¶¶0041-52) obtaining transaction data associated with an account used in a transaction at a retail enterprise; (¶0051) identify one or more nodes within the identity graph that correspond to one of a plurality of possible identity matches by performing a deterministic matching process between the transaction data and the one or more nodes, wherein the deterministic matching process identifies a correspondence between identifying attributes included in the transaction data with identifying attributes of customer accounts associated with the respective one or more nodes, the plurality of possible identity matches being based at least in part on geographic proximity between a location represented in the transaction data and locations represented in transaction data associated with the one or more nodes; (¶0051 and ¶0062) for each of the one or more nodes, provide the transaction data and an identification of the node to a machine learning model to obtain a determination, the machine learning model being trained using training transaction data linked to the customer accounts corresponding to user profile nodes in the identity graph; (Fig. 4; ¶¶0005-6; ¶0057) based, at least in part, on a determination from the machine learning model that the transaction data is associated with a node of the one or more nodes, establish an identity edge between the node and a user profile node corresponding to the account, thereby adding the user profile node corresponding to the account to a cluster that includes the node. (¶0048 and ¶0050) However, the prior art does not teach the following: a plurality of user clusters, each user cluster being associated with a different customer and including one or more user profile nodes, wherein a customer account comprises a plurality of identifying attributes of the customer and each user profile node corresponds to a different manner in which the customer interacts with a retail enterprise; wherein the machine learning model is a classifier model; wherein the determination of whether the transaction data is associated with the node based on a selected threshold probability score; wherein the probability score represents an extent of similarity between the transaction data and the node.
Conclusion
The following prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US10523682B1 (“Badawy et al.”) discloses systems and methods for embodiments of a graph based artificial intelligence systems for identity management are disclosed . Embodiments of the identity management systems disclosed herein may utilize a network graph approach to analyzing identities or entitlements of a distributed net worked enterprise computing environment . Specifically , in certain embodiments , an artificial intelligence based identity governance systems may include an intelligent decision support agent to provide an approval or denial recommend dation for an access request . To provide an approval or denial recommendation , the intelligent agent may utilize a classifier trained on historical certification data . The intelligent agent may utilize features which represent relevant signals to the approval or denial decision including features that may be associated with a network graph of the identities and entitlements of the enterprise computing environment.
US20200311746A1 (“Parida et al.”) discloses a method for providing analytics for a physical customer based on processed remote transactions includes: storing transaction data entries, each including a time, date, additional value, and data; receiving a notification including a detection time, detection date, and identification value; identifying a first transaction data entry where the date matches the detection date, the additional value matches the identification value, and the time is within a predetermined period of the detection time; identifying a subset of transaction data entries related to the first transaction data entry based on a correspondence in at least one of: the additional value and the transaction data included in the first transaction data entry and each entry in the subset; determining analytics based on the transaction data included in the subset; and transmitting the analytics to a third party device.
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/YINGYING ZHOU/Examiner, Art Unit 3697