Analysis of third party networks

• US 8,356,052 B2
• Filed: 03/15/2012
• Issued: 01/15/2013
• Est. Priority Date: 02/12/2002
• Status: Active Grant

• Current Assignee: Mantas, Inc. (Oracle Corporation)
• Original Assignee: Mantas, Inc. (Oracle Corporation)
• Inventors: Zhang, Tao, Donoho, Steven Kirk
• Primary Examiner(s): Colbert, Ella
• Application Number:
  US13/420,864
• Publication Number:
  US 20120173723A1
• Time in Patent Office: 306 Days
• Field of Search: 705/1, 705/1.1, 705/36, 705/36.R, 705/35, 705/44, 707/760, 707/776, 707/780, 707/800, 707/950, 709/203, 709/217, 709/218
• US Class Current: 707/776
• CPC Class Codes: G06Q 10/067 Enterprise or organisation modelling
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/06 Buying, selling or leasing transactions
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis
• CPC Class Codes: Y10S 707/95 Financial

Abstract

A method of analyzing customer behavior, where customers are engaged in customer-to-customer transactions in a third-party network, includes a transformation of data representing the customer-to-customer transactions from a data representation to a network representation, and then analyzing the network representation. The network representation includes a set of nodes and a set of links where each node represents a customer and each link represents a transaction between two of the customers.

Claims

1. A method of monitoring network activity, the method comprising:

monitoring a plurality of transactions that occur at least partially in a first network;

monitoring a plurality of transactions that occur at least partially in a second network;

storing, in a computer program memory, a plurality of node, each node comprising data indicative of a participant in a transaction of the plurality of transactions;

storing, in the computer program memory, a plurality of links, each link is associated with two nodes, and each link comprises data indicative of a measurement associated with the transaction between the participants associated with the same two nodes;

transforming the data indicative of a measurement associated with the transaction between the participants associated with the same two nodes from a data representation into a network representation; and

analyzing the network representation to identify at least one transaction pattern within the network representation.

2. The method of claim 1, wherein each transaction comprises a transaction between two parties.

3. The method of claim 1, wherein each transaction comprises a transfer of funds.

4. The method of claim 1, wherein the data indicative of a measurement comprises a Customer Identification (ID) and an account identification (ID).

5. The method of claim 1, wherein the data indicative of a measurement comprises a measure of transaction value, a measure of funds, a measure of time, a measure of distance between the participants associated with the nodes, or a measure of transaction frequency.

6. The method of claim 1, further comprising analyzing the links to identify at least one group transaction patterns.

7. The method of claim 6, further comprising detecting a link that deviates from the at least one group transaction patterns.

8. The method of claim 6, further comprising detecting a link that corresponds to a pre-identified transaction pattern.

9. The method of claim 1, further comprising:

analyzing the links to identify at least one intra-network group transaction pattern; and

analyzing the links to identify at least one extra-network group transaction pattern.

10. The method of claim 9, further comprising detecting a link that does not conform to any applicable group transaction pattern.

11. The method of claim 9, further comprising detecting a link that corresponds to a pre-identified transaction pattern.

12. A non-transitory computer-readable medium for monitoring network activity, having sets of instructions stored thereon which, when execute by a computer, cause the computer to:

monitor a plurality of transactions that occur at least partially in a first network;

monitor the plurality of transactions that occur at least partially in a second network;

store, in a computer program memory, a plurality of nodes, each node comprising data indicative of a participant in a transaction of the plurality of transactions;

store, in the computer program memory, a plurality of links, each link is associated with two nodes, and each link comprises data indicative of a measurement associated with the transaction between the participants associated with the same two nodes;

transform the data indicative of a measurement associated with the transaction between the participants associated with the same two nodes from a data representation into a network representation; and

analyze the network representation to identify at least one transaction pattern within the network representation.

13. The non-transitory computer-readable medium of claim 12, wherein each transaction comprises a transaction between two parties.

14. The non-transitory computer-readable medium of claim 12, wherein each transaction comprises a transfer of funds.

15. The computer-readable medium of claim 12, wherein the data indicative of a measurement comprises a Customer Identification (ID) or an account identification (ID).

16. The non-transitory computer-readable medium of claim 12, wherein the data indicative of a measurement comprises a measure of transaction value, a measure of funds, a measure of time, a measure of distance between the participants associated with the nodes, or a measure of transaction frequency.

17. A system for monitoring network activity, the system comprising:

a storage device; and

at least one processor in communication with the storage device, wherein the storage device has sets of instructions stored thereon which, when execute by the at least one processor, cause the at least one processor to;

monitor a plurality of transactions that occur at least partially in a first network;

monitor a plurality of transactions that occur at least partially in a second network;

store, in a computer program memory, a plurality of nodes, each node comprising data indicative of a participant in a transaction of the plurality of transactions;

store, in the computer program memory, a plurality of links, each link is associated with two nodes, and each link comprises data indicative of a measurement associated with the transaction between the participants associated with the same two nodes;

transform the data indicative of a measurement associated with the transaction between the participants associated with the same two nodes from a data representation into a network representation; and

analyze the network representation to identify at least one transaction pattern within the network representation.

18. The system of claim 17, wherein the sets of instructions when further executed by the at least one processor, cause the at least one processor to analyze the links to identify at least one group transaction patterns.

19. The system of claim 18, wherein the sets of instructions when further executed by the at least one processor, cause the at least one processor to detect a link that deviates from the at least one group transaction patterns.

20. The system of claim 18, wherein the sets of instructions when further executed by the at least one processor, cause the at least one processor to detect a link that corresponds to a pre-identified transaction pattern.