DETAILED ACTION
Claims 1-11 and 29-31 are pending.
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Examiner’s Notes
Examiner has cited particular columns and line numbers, paragraph numbers, or figures in the references as applied to the claims below for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested from the applicant, in preparing the responses, to fully consider the references in entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner.
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 1-11 and 29-31 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Statutory Category: Claims 1, 29, 30 and 31 are directed to a method, system, apparatus and non-transitory computer-readable storage medium system and method. Therefore, the claims are directed to one of the four statutory categories of inventions.
Step 2A – Prong 1: Claims 1, 29, 30 and 31 recites, creating a plurality of entity vertices and corresponding entity account vertices of the entity vertices; creating an owning relationship between the entity vertices and the corresponding entity account vertices; determining a start point entity account vertex set and an endpoint entity account vertex set based on the created entity account vertices, wherein there is no overlapping entity account vertex between the start point entity account vertex set and the endpoint entity account vertex set; and creating an account association relationship between the entity account vertices based on the start point entity account vertex set and the endpoint entity account vertex set.. These limitations as drafted, is a process that, under their broadest reasonable interpretation, covers an abstract idea such as performance of the limitation in the mind. That is, other than a generic computer, nothing in the claim elements precludes the steps from practically being performed mentally. Specifically, creating can be performed mentally through observation, evaluation, judgement, opinion by a developer to create the vertices for a graph and determining can be done by a developer to determine start and end points. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the category mental process grouping of abstract idea. Accordingly, the claim recites an abstract idea under step 2A prong 1.
Step 2A, Prong 2: The additional elements do not integrate the judicial exception into a practical application. The limitations a system for generating graph data to be applied to a benchmark test, comprising: a least two first devices, wherein a vertex generation framework is deployed at each first device, at least two second devices, wherein a vertex relationship generation framework is deployed at each second device; and a third device at which a vertex block framework is deployed, wherein each vertex generation framework is configured to recites field of use/technological environment, see MPEP 2106.05(h) and the vertex block framework is configured to extract, recites insignificant extra-solution activity of data gathering, see MPEP 2106.05(g). The limitations an apparatus for generating graph data to be applied to a benchmark test comprising memory and a processor, wherein the memory stores executable instructions that, in response to execution by the processor, cause the processor and a non-transitory computer-readable storage medium comprising instructions stored therein that, when executed by a processor of a computing device, cause the processor recite mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, see MPEP 2106.05(f). Accordingly, the additional elements recited in the claims do not integrate the abstract idea into a practical application.
Step 2B: As discussed with respect to step 2A prong 2, the additional elements an apparatus for generating graph data to be applied to a benchmark test comprising memory and a processor, wherein the memory stores executable instructions that, in response to execution by the processor, cause the processor and a non-transitory computer-readable storage medium comprising instructions stored therein that, when executed by a processor of a computing device, cause the processor. The limitations an apparatus for generating graph data to be applied to a benchmark test comprising memory and a processor, wherein the memory stores executable instructions that, in response to execution by the processor, cause the processor and a non-transitory computer-readable storage medium comprising instructions stored therein that, when executed by a processor of a computing device, cause the processor amount to well-understood, routine conventional activities as seen in court cases storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93 and receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information). Accordingly, the claim does not amount to significantly more than the judicial exception, thus lack an inventive concept for patent eligibility under 35 USC 101.
Regarding claims 2-3, 5-7 and 10, the additional elements fall under an abstract idea. Regarding claim 4, obtaining vertex degree recites to insignificant extra-solution activity of data gathering, see MPEP 2106.05(g) and creating recites an abstract idea. Regarding claim 8, obtaining vertex outdegree/indegree recites to insignificant extra-solution activity of data gathering, see MPEP 2106.05(g) and determining recites an abstract idea. Regarding claim 9, obtaining social network outdegree/indegree recites to insignificant extra-solution activity of data gathering, see MPEP 2106.05(g) and determining a relationship recites an abstract idea. Regarding claim 11, extracting a plurality of first entity vertices recites to insignificant extra-solution activity of data gathering, see MPEP 2106.05(g) and creating recites an abstract idea. Thus, these limitations do not integrate the judicial exception into a practical application under prong 2, or amounts to significantly more under Step 2B.
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 (i.e., changing from AIA to pre-AIA ) 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.
Claim(s) 1-4, 29-31 are rejected under 35 U.S.C. 103 as being unpatentable over Chari et al. (US-PGPUB-NO: 2017/0140382 A1) hereinafter Chari, in further view of Thomson et al. (US-PGPUB-NO: 2018/0351825 A1) hereinafter Thomson.
As per claim 1, Chari teaches a method for generating graph data to be applied to a benchmark test, comprising: creating a plurality of entity vertices and corresponding entity account vertices of the entity vertices (see Chari paragraph [0085], “In this example, transaction payment relationship graph 300 includes source account vertex 302 and destination account vertex 304. Source account vertex 302 represents account “1234” and destination account vertex 304 represents account “5678””); creating an owning relationship between the entity vertices and the corresponding entity account vertices (see Chari paragraph [0085], “Accounts “1234” and “5678” have multiple transactions 306 performed between them. Illustrative embodiments label each transaction in multiple transactions 306 between accounts “1234” and “5678” with a timestamp, such as timestamp 308 “2014-12-02 13:20:50” and an amount, such as amount 310 “$3.25””).
Chari does not explicitly teach determining a start point entity account vertex set and an endpoint entity account vertex set based on the created entity account vertices, wherein there is no overlapping entity account vertex between the start point entity account vertex set and the endpoint entity account vertex set; and creating an account association relationship between the entity account vertices based on the start point entity account vertex set and the endpoint entity account vertex set. However, Thomson teaches determining a start point entity account vertex set and an endpoint entity account vertex set based on the created entity account vertices, wherein there is no overlapping entity account vertex between the start point entity account vertex set and the endpoint entity account vertex set (see Thomson [0058], “In an embodiment, the walk manager may dynamically perform the walk executed with respect to FIG. 2A by first loading a previous intermediate state of the walk at vertex 206. As discussed with respect to FIG. 1, the intermediate state of a walk at, vertex 206 may include messages received by vertex 206, which may include the starting vertex of the walk and the path of vertices and edges traversed before arriving at the vertex 206. With this intermediate state of the walk located, the walk manager may perform the walk as normal from vertex 206 by examining the walk definition in the walk customization document. In the depicted example, the walk manager may again send a message from vertex 206 to vertex 214, which may include the data updated with respect to vertex 206. However, because the edge has been deleted, no message will be sent from vertex 206 to vertex 212. The walk may continue to vertex 216 before terminating, and the ending procedure for the walk, may be re-executed taking into account the updated data and vertices traversed by the walk”); and creating an account association relationship between the entity account vertices based on the start point entity account vertex set and the endpoint entity account vertex set (see Thomson [0062], “At stage 308, linking rules may be retrieved from, a provider-specific customization document. Linking rules may he used to determine source and destination endpoints on the vertex based on the data associated with the vertex. Each endpoint may be defined to include the name or other identifier of the linking rule used and at least one data attribute of the vertex. Each linking rule may specify a relationship between a data attribute of a first entity type and a data attribute of a second entity type. Each rule may have a unique name or other identifier and specify a source entity type and data attribute of that entity, and a destination entity type and data attribute of that entity. For example, a linking rule may specify that a network entity of type router that includes a particular IP address (source) be connected to a network entity of type port that has a matching IP address (destination). This linking rule may create a directed edge in the network graph from the vertex representing the router to the vertex representing the port. In an embodiment, a linking rule may specify a relationship between more than two entity types or contain logic involving multiple entity types within a relationship. For example, a provider may use two different entity types across different data sources that represent variations both applicable to the rule”).
Chari and Thomson are analogous art because they are in the same field of endeavor of software development. Therefore, it would have been obvious to one or more person of ordinary skills in the art before the effective filing date of the claimed invention to modify Chari’s teaching automatically identifying fraudulent transactions by predicting a probability that an edge exists between two vertices with Thomson’s teaching of providing network management and application services for a telecommunication network to incorporate start and end points for vertices to track interactions between the vertices and associating said points with identifiers, see Thomson paragraph [0013], “The received data may be associated with a first vertex in the network graph. A rule specifying a relationship between a data attribute of a first entity type and a data attribute of a second entity type may then be retrieved from a provider-specific customization document. The plurality of edges in the network graph connected to the first vertex may be updated based on the rule, and a walk associated with the first vertex may be identified. The walk may have a walk definition that specifies the entity, type of the starting vertex, the traversable edge types, and instructions on what output entities to generate. The identified walk may then be dynamically executed from an intermediate starting vertex to generate one or more output entities”.
As per claim 2, Chari modified with Thomson teaches wherein an account vertex attribute of each entity account vertex comprises an account association attribute, and the method further comprises: creating an account attribute vertex based on the account association attribute of each entity account vertex (see Thomson paragraph [0063], “At stage 310, the edges in the network graph connected to the vertex identified at stage 306 may be updated based on the retrieved rules. To accomplish this, the source and destination endpoints of the vertex may be compared with source and destination endpoints of existing vertices within the network graph”); and creating an account attribute relationship between account attribute vertices and/or between each account attribute vertex and a corresponding entity account vertex based on the account association attribute (see Thomson paragraph [0063], “When a match between the data attributes specified by a linking rule is found between an endpoint of the vertex associated with the received data and an endpoint of another vertex in the network graph, an edge may be created between the two vertices. Similarly, if an edge previously existed between the vertex associated with the received data and another vertex, stage 310 may detect when a match is no longer found between endpoints of the two vertices and remove the edge from the network graph. This scenario may occur when data received from a provider-specific data source updates the values of one or more data attributes of the vertex”).
As per claim 3, Chari modified with Thomson teaches wherein the entity vertex comprises a personal vertex and an organizational vertex, the entity account vertex comprises a personal account vertex and an organizational account vertex, and the account attribute vertex comprises at least one of an account registration address, a registration phone, a login network address, and a login physical address; and the account attribute relationship comprises at least one of a location relationship, a phone registration relationship, a login network address relationship, and a login physical address relationship (see Chari paragraph [0086], “Transaction payment relationship graph 300 also shows transaction 312 between account “5678” and a point-of-sale terminal, which corresponds to point-of-sale terminal vertex 314. “ACME STORE 123 MAIN STREET, CITY, STATE” is the label for point-of-sale terminal vertex 314 that uniquely identifies the point-of-sale terminal and its physical location. Similarly, account “1234” performs transaction 316 with an automated teller machine corresponding to automated teller machine vertex 318 labeled “1234.CASH”. Transaction 316 indicates that an owner of account “1234” has withdrawn some money from account “1234”. Transactions 312 and 316 do not show an amount or a timestamp, which are features for the edges inserted between the vertices”).
As per claim 4, Chari modified with Thomson teaches further comprising: obtaining vertex outdegree distribution information of the entity vertices (see Chari paragraph [0123], “The process begins when the data processing system identifies a source account vertex corresponding to a source account and a destination account vertex corresponding to a destination account associated with a current financial transaction in a transaction payment relationship graph (step 1402). In addition, the data processing system calculates an out-degree of the source account vertex and an in-degree of the destination account vertex in the transaction payment relationship graph (step 1404)”); and creating corresponding entity account vertices of the entity vertices comprises: creating the corresponding entity account vertices of the entity vertices based on the vertex outdegree distribution information (see Chari paragraph [0124], “Further, the data processing system calculates an out-degree distribution of the transaction payment relationship graph (step 1406). The data processing system also calculates an in-degree distribution of the transaction payment relationship graph (step 1408). Furthermore, the data processing system calculates a probability that an edge exists between the source account vertex and the destination account vertex based on the out-degree of the source account vertex, the out-degree distribution of the transaction payment relationship graph, the in-degree of the destination account vertex, and the in-degree distribution of the transaction payment relationship graph (step 1410). Thereafter, the process terminates”).
As per claim 11, Chari modified with Thomson teaches further comprising: extracting a plurality of first entity vertices from the plurality of entity vertices (see Chari paragraph [0045], “Graph feature extraction component 226 extracts graph features 238 from transaction payment relationship graphs 236”); and creating corresponding entity account vertices of the entity vertices comprises: creating corresponding entity account vertices of the first entity vertices (see Chari paragraph [0045], “In response to vertex link prediction component 228 receiving current account transaction data 240, vertex link prediction component 228 retrieves information regarding extracted graph features 238 from graph feature extraction component 226 for use in generating vertex link prediction 242 for the current financial transaction being performed. Current account transaction data 240 are information corresponding to a current financial transaction being transacted between financial accounts. Vertex link prediction 240 is a percentage probability that an edge exists between two vertices in transaction payment relationship graphs 236 corresponding to current account transaction data 240. After vertex link prediction component 228 generates vertex link prediction 242, vertex link prediction component 228 forwards vertex link prediction 242 to transaction scoring component 230”).
As per claim 29, this is the system claim to method claim 1. Therefore, it is rejected for the same reasons as above.
As per claim 30, this is the apparatus claim comprising a memory and a processor, wherein the memory stored executable instructions (see Chari paragraph [0039], “Processor unit 204 serves to execute instructions for software applications and programs that may be loaded into memory 206. Processor unit 204 may be a set of one or more hardware processor devices or may be a multi-processor core, depending on the particular implementation. Further, processor unit 204 may be implemented using one or more heterogeneous processor systems, in which a main processor is present with secondary processors on a single chip. As another illustrative example, processor unit 204 may be a symmetric multi-processor system containing multiple processors of the same type”) to method claim 1. Therefore, it is rejected for the same reasons as above.
As per claim 31, this is the non-transitory computer-readable storage medium comprising instructions stored therein (see Chari paragraph [0022], “Computer readable program instructions described herein can be downloaded to respective computing/processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and/or a wireless network. The network may comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. A network adapter card or network interface in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing/processing device”) claim to method claim 1. Therefore, it is rejected for the same reasons as above.
Claim(s) 5, 8 and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Chari (US-PGPUB-NO: 2017/0140382 A1) and Thomson (US-PGPUB-NO: 2018/0351825 A1), in further view of Li (US-PGPUB-NO: 2021/0357942 A1).
As per claim 5, Chari modified with Thomson teaches wherein an account vertex attribute of each entity account vertex comprises a vertex outdegree and a vertex indegree (see Chari paragraph [0123], “The process begins when the data processing system identifies a source account vertex corresponding to a source account and a destination account vertex corresponding to a destination account associated with a current financial transaction in a transaction payment relationship graph (step 1402). In addition, the data processing system calculates an out-degree of the source account vertex and an in-degree of the destination account vertex in the transaction payment relationship graph (step 1404)”), and the creating an account association relationship between the entity account vertices based on the start point entity account vertex set and the endpoint entity account vertex set comprises: determining a selection probability of each start point entity account vertex in the start point entity account vertex set and a selection probability of each endpoint entity account vertex in the endpoint entity account vertex set based on a vertex outdegree of each start point entity account vertex and a vertex indegree of each endpoint entity account vertex (see Chari paragraph [0124], “Further, the data processing system calculates an out-degree distribution of the transaction payment relationship graph (step 1406). The data processing system also calculates an in-degree distribution of the transaction payment relationship graph (step 1408). Furthermore, the data processing system calculates a probability that an edge exists between the source account vertex and the destination account vertex based on the out-degree of the source account vertex, the out-degree distribution of the transaction payment relationship graph, the in-degree of the destination account vertex, and the in-degree distribution of the transaction payment relationship graph (step 1410). Thereafter, the process terminates”).
Chari modified with Thomson do not explicitly teach selecting at least one start point entity account vertex and a corresponding endpoint entity account vertex from the start point entity account vertex set and the endpoint entity account vertex set based on the selection probability of each start point entity account vertex and the selection probability of each endpoint entity account vertex; calculating an attribute distance between the selected start point entity account vertex and corresponding endpoint entity account vertex; determining a relationship creation probability between the selected start point entity account vertex and corresponding endpoint entity account vertex based on the calculated attribute distance; and creating an account association relationship between the selected start point entity account vertex and corresponding endpoint entity account vertex based on the relationship creation probability. However, Li teaches selecting at least one start point entity account vertex and a corresponding endpoint entity account vertex from the start point entity account vertex set and the endpoint entity account vertex set based on the selection probability of each start point entity account vertex and the selection probability of each endpoint entity account vertex (see Li paragraph [0057], “Each vertex in the medium network can have a risk value, which can be updated in real-time based on changes and updates to the medium network. The risk value can represent the probability, determined at the current point of time, that the vertex is a dangerous entity (such as a fraudulent entity or an impersonated entity)”); calculating an attribute distance between the selected start point entity account vertex and corresponding endpoint entity account vertex (see Li paragraph [0058], “A medium network is usually constructed from a black seed. A type of the black seed (also referred to as a seed) is the same as a type of a vertex (such as a bank account, a mobile number, an ALIPAY account, or a WeChat account) in the medium network, and the black seed represents an entity that has been determined to have a certain type of risk, such as an entity with poor credit or with a fraud, embezzlement, or impersonation history”); determining a relationship creation probability between the selected start point entity account vertex and corresponding endpoint entity account vertex based on the calculated attribute distance (see Li paragraph [0059], “In the present specification, multi-media (or multi-path) association with a black seed, an additional risk feature, a degree of association with the black seed, a vertex overlapping degree during stacking of multiple medium networks are considered concurrently in determining a risk value of a vertex in a medium network, so that the risk value can be more accurately determined, to more accurately identify a high-risk vertex, in real-time and prior to potential transactions”); and creating an account association relationship between the selected start point entity account vertex and corresponding endpoint entity account vertex based on the relationship creation probability (see Li paragraph [0057], “Each vertex in the medium network usually can include one or more types of risk values (such as a fraud risk value and an impersonation risk value). A value of a vertex about a certain type of risk can represent the probability of risk occurrence with the vertex, as determined at the current point of time”).
Chari, Thomson and Li are analogous art because they are in the same field of endeavor of software development. Therefore, it would have been obvious to one or more person of ordinary skills in the art before the effective filing date of the claimed invention to modify Chari’s teaching automatically identifying fraudulent transactions by predicting a probability that an edge exists between two vertices and Thomson’s teaching of providing network management and application services for a telecommunication network with Li’s teaching of identifying high risk vertices to incorporate selecting different points and calculating relationship between the points to determine risk values between vertices to find possible fraud , see Li paragraph [0035], “The medium network construction and high-risk node identification of the present specification can be applied to various scenarios for determining risky transactions such as a forbidden risk, a fraud risk, and a marketing risk, and can achieve significant effects”.
As per claim 8, Chari modified with Thomson and Li teaches further comprising: obtaining vertex outdegree/indegree distribution information of the entity account vertex (see Chari paragraph [0123], “The process begins when the data processing system identifies a source account vertex corresponding to a source account and a destination account vertex corresponding to a destination account associated with a current financial transaction in a transaction payment relationship graph (step 1402). In addition, the data processing system calculates an out-degree of the source account vertex and an in-degree of the destination account vertex in the transaction payment relationship graph (step 1404)”); and determining the vertex outdegree and the vertex indegree of each entity account vertex based on the vertex outdegree/indegree distribution information (see Chari paragraph [0127], “Afterward, the data processing system makes a determination as to whether the likelihood of fraud is high (step 1510). If the data processing system determines that the likelihood of fraud is high, yes output of step 1510, then the data processing system makes another determination as to whether the out-degree distribution or the in-degree distribution is high (step 1512). If the data processing system determines that the out-degree distribution or the in-degree distribution is low, no output of step 1512, then the data processing system identifies the current financial transaction as a fraudulent financial transaction (step 1514). Thereafter, the process terminates”).
As per claim 10, Chari modified with Thomson and Li teaches wherein creating the corresponding entity account vertices of the plurality of entity vertices based on the vertex outdegree distribution information comprises: creating the corresponding entity account vertices and service application vertices of the entity vertices based on the vertex outdegree distribution information (see Li paragraph [0068], “The fourth part is multi-network stacking: The multiple independent medium networks are stacked together, and a multi-media structure is constructed for an overlapped vertex to form a multilateral structure. A third risk value is determined for a vertex in the multi-media structure, to obtain a final risk value. A potential high-risk vertex is determined based on the final risk value. Further, the high-risk vertex can be added to the black seed pool based on final risk value distribution and expert experience, to form a complete benign identification system”); and creating an application relationship between each service application vertex and a corresponding entity vertex (see Li paragraph [0069], “The third part and/or fourth part can be interactively repeated or otherwise triggered for updating based on real-time changes to the networks in accordance with concurrently monitored status of the different media. In some embodiments, various functions related to at least a subset of the monitoring of media, updating of media networks, the third part, and the fourth part can be performed in parallel”).
Claim(s) 6 and 7 are rejected under 35 U.S.C. 103 as being unpatentable over Chari (US-PGPUB-NO: 2017/0140382 A1), Thomson (US-PGPUB-NO: 2018/0351825 A1) and Li (US-PGPUB-NO: 2021/0357942 A1), in further view of Naccache et al. (US-PGPUB-NO: 2018/0129700 A1) hereinafter Naccache.
As per claim 6, Chari modified with Thomson and Li do not explicitly teach wherein a process of creating the account association relationship is cyclically performed until no new account association relationship is created, and a relationship creation probability used in each cycle process is obtained by performing attenuation processing on a relationship creation probability in a previous cycle process. However, Naccache teaches wherein a process of creating the account association relationship is cyclically performed until no new account association relationship is created (see Naccache paragraph [0054], “Usually, the value of the balance (b) is equal to zero. Thus, it is then possible to identify the groups of records which cancel themselves, which are groups of records for which the balance is null between a given numbers of users (in one group). In the case of bitcoins, for example, this would be a given number of transactions between several users, forming a group, for which from the point of view of every user in the group, the balance of the values of transaction is equal to zero, which means that every user in the group has given as much than he has received. Groups may be for example cycles (loop) and/or cliques of records, these records being strongly connected with each other”), and a relationship creation probability used in each cycle process is obtained by performing attenuation processing on a relationship creation probability in a previous cycle process (see Naccache paragraph [0019-0021], “According to the disclosure, said step for removing, inside said subgraph, at least one vertex, comprises, for said at least one vertex: [0020] when the number of incoming edges or the number of outgoing edges of said vertex is equal to zero, deleting said vertex; [0021] when the number of outgoing edges and the number of incoming edges is equal to one and the value of the single outgoing edge is different from the value of the incoming edge, deleting said vertex”).
Chari, Thomson, Li and Naccache are analogous art because they are in the same field of endeavor of software development. Therefore, it would have been obvious to one or more person of ordinary skills in the art before the effective filing date of the claimed invention to modify Chari’s teaching automatically identifying fraudulent transactions by predicting a probability that an edge exists between two vertices, Thomson’s teaching of providing network management and application services for a telecommunication network and Li’s teaching of identifying high risk vertices with Naccache’s teaching of reducing an amount of records in a database to incorporate data reduction by purging a set of transactions.
As per claim 7, Chari modified with Thomson, Li and Naccache teaches wherein a process of selecting the start point entity account vertex and the corresponding endpoint entity account vertex and a process of creating the account association relationship are cyclically performed until a quantity of created account association relationships reaches a predetermined quantity (see Naccache paragraph [0054], “Usually, the value of the balance (b) is equal to zero. Thus, it is then possible to identify the groups of records which cancel themselves, which are groups of records for which the balance is null between a given numbers of users (in one group). In the case of bitcoins, for example, this would be a given number of transactions between several users, forming a group, for which from the point of view of every user in the group, the balance of the values of transaction is equal to zero, which means that every user in the group has given as much than he has received. Groups may be for example cycles (loop) and/or cliques of records, these records being strongly connected with each other”).
Allowable Subject Matter
Claim 9 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Hunter (US-PGPUB-NO: 2021/0149958 A1) teaches graph outcome determination in domain-specific execution environment.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to LENIN PAULINO whose telephone number is (571)270-1734. The examiner can normally be reached Week 1: Mon-Thu 7:30am - 5:00pm Week 2: Mon-Thu 7:30am - 5:00pm and Fri 7:30am - 4:00pm EST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Bradley Teets can be reached at (571) 272-3338. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/LENIN PAULINO/Examiner, Art Unit 2197
/BRADLEY A TEETS/Supervisory Patent Examiner, Art Unit 2197