ANALYSIS OF THIRD PARTY NETWORKS

• US 20100223199A1
• Filed: 05/11/2010
• Published: 09/02/2010
• Est. Priority Date: 02/12/2002
• Status: Active Grant

• Current Assignee: Steven Kirk Donoho, Tao Zhang
• Original Assignee: Steven Kirk Donoho, Tao Zhang
• Inventors: Zhang, Tao, Donoho, Steven Kirk
• Granted Patent: US 8,161,062 B2
• Time in Patent Office: Days
• US Class Current: 705/348
• 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 the third-party network, includes the 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 analyzing characteristics or behaviors of customers engaged in customer-to-customer transactions in a third party network, comprising the steps of:

transforming data representative of a plurality of individual customer-to-customer transactions from a data representation to a network representation; and

performing third-party network analysis on the network representation.

2. The method of claim 1, further including the step of building one or more third-party networks corresponding to customer-to-customer transactions.

3. The method of claim 2, wherein each third-party network comprises a plurality of nodes and a plurality of links, wherein each node is associated with at least one link and each link is associated with at least two nodes.

4. The method of claim 3, wherein each node in a network represents a member, customer or individual involved in third-party business activity.

5. The method of claim 3, wherein each link represents a connection or transaction between two member customers.

6. The method of claim 2, wherein each third-party network represents a group of customers connected through customer-to-customer transactions.

7. The method of claim 2, wherein each network has internal link pattern characteristics corresponding to interactions and connections between member customers in the network.

8. The method of claim 2, wherein each network has external network pattern characteristics, representing interactions and relationships between a network and external entities outside the network.

9. The method of claim 1, wherein the performing step comprises analyzing third-party networks, wherein each third-party network represents a group of customers connected through customer-to-customer transactions.

10. The method of claim 9, wherein the step of analyzing third-party networks identifies internal characteristics and behaviors of each network.

11. The method of claim 9, wherein the step of analyzing third-party networks identifies external characteristics and behaviors of each network by treating each network as a network object.

12. The method of claim 9, wherein the performing step further comprises the step of network mining using one or more mining algorithms.

13. The method of claim 12, wherein the network mining step comprises using decision tree mining to store third-party network patterns in nodes.

14. The method of claim 13, wherein at least one of the nodes stores a subset of networks having similar group pattern behaviors.

15. The method of claim 12, wherein the network mining step comprises using association rule mining to find networks having important association relationships with external patterns outside networks.

16. The method of claim 12, wherein the network mining step comprises using clustering group networks having similar network properties.

17. The method of claim 12 wherein the network mining step comprises detecting transactions that correspond to a pattern.

18. The method of claim 12 wherein the network mining step comprises detecting transactions that deviate from a pattern.

19-20. -20. (canceled)

21. A method of monitoring activity in a network, comprising:

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

storing, in a computer program memory, a plurality of nodes, wherein each node comprises data indicative of a participant in one or more of the transactions; and

storing, in the computer program memory, a plurality of links, wherein 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.

22. The method of claim 21 wherein each transaction comprises a transaction between two parties.

23. The method of claim 21 wherein each transaction comprises a transfer of funds.

24. The method of claim 21 wherein the data indicative of a measurement comprises a customer ID or an account ID.

25. The method of claim 21 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.

26. The method of claim 21 comprising the additional step of analyzing the links to identify at least one group transaction pattern.

27. The method of claim 26 comprising the additional step of detecting a link that deviates from the at least one group transaction pattern.

28. The method of claim 26 comprising the additional step of detecting a link that corresponds to a pre-identified transaction pattern.

29. The method of claim 21 comprising the additional steps of:

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.

30. The method of claim 29 comprising the additional step of detecting a link that does not conform to any applicable group transaction pattern.

31. The method of claim 29 comprising the additional step of detecting a link that corresponds to a pre-identified transaction pattern.