RELATIONSHIP GRAPH

• US 20170286565A1
• Filed: 06/20/2017
• Published: 10/05/2017
• Est. Priority Date: 06/23/2011
• Status: Active Grant

• Current Assignee: FullContact, Inc.
• Original Assignee: FullContact, Inc.
• Inventors: Brave, Scott, Lynn, Daniel Kenton
• Granted Patent: US 10,445,371 B2
• Time in Patent Office: Days
• CPC Class Codes: G06F 16/2458 Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
• CPC Class Codes: G06F 16/288 Entity relationship models
• CPC Class Codes: G06F 16/9024 Graphs; Linked lists G06F16/9027 takes precedence
• CPC Class Codes: G06Q 10/00 Administration; Management
• CPC Class Codes: G06Q 10/107 Computer-aided management of electronic mailing [e-mailing]

Abstract

A relationship graph system disclosed herein provides a system and method for inferring relationships between various entities based on analysis of a plurality of observations including elements related to two different entities. The method comprises representing each of the plurality of observations using a relationship edge between two nodes, each of the two nodes representing an element related to one of the two different entities, assigning a score to each relationship edge based on metadata related to the observation represented by the relationship edge, combining a plurality of relationship edges between the elements related to the two different entities to generate an aggregate relationship edge between the two different entities, and inferring a relationship between the two different entities based on length of the aggregate relationship edge between the two different entities.

Claims

1. A computer implemented method comprising:

analyzing a plurality of observations including elements related to two different entities;

representing each of the plurality of observations using a relationship edge between two nodes, each of the two nodes representing an element related to one of the two different entities;

assigning a score to each relationship edge based on metadata related to the observation represented by the relationship edge;

combining a plurality of relationship edges between the elements related to the two different entities to generate an aggregate relationship edge between the two different entities; and

inferring a relationship between the two different entities based on length of the aggregate relationship edge between the two different entities.

2. The method of claim 1, further comprising computing the length of the aggregate relationship edge between the two different entities by:

computing length of each of the plurality of relationship edges between the elements related to the two different entities; and

computing the length of the aggregate relationship edge between the two different entities using a combination of the length of each of the plurality of relationship edges between the elements related to the two different entities.

3. The method of claim 1, wherein assigning a score to each relationship edge further comprises assigning a score based on recency of the observation represented by the relationship edge.

4. The method of claim 1, further comprising assigning a trustworthiness score to each of the plurality of observations.

5. The method of claim 4, wherein assigning a score to each relationship edge further comprising assigning the score based on the trustworthiness score of the observation represented by the relationship edge.

6. The method of claim 1, further comprising combining one or more of the plurality of relationship edges between the elements related to the two different entities with one or more of identification edges related to the nodes of the one or more of the plurality of relationship edges.