SYSTEM AND METHOD FOR COMBINING DATA FOR IDENTIFYING COMPATIBILITY

• US 20140108308A1
• Filed: 07/11/2013
• Published: 04/17/2014
• Est. Priority Date: 07/13/2012
• Status: Abandoned Application

• Current Assignee: Social Data Technologies LLC
• Original Assignee: Social Data Technologies LLC
• Inventors: Stout, Ryan, Cantino, Andrew
• Application Number:
  US13/939,951
• Publication Number:
  US 20140108308A1
• Time in Patent Office: Days
• US Class Current: 706/12
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 3/08 Learning methods
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 30/0241 Advertisements
• CPC Class Codes: G06Q 50/01 Social networking

Abstract

A method and system for combining data for identifying compatibility, having the steps of accessing at least one data source to extract data from the at least one data source that substantially merges all user data, classifying the data using a classification system, generating a data vector for the data, storing the data vector in the classification system, assessing a user attribute vector to the user data, comparing the data vector and the user attribute vector to produce at least one relationship recommendation, and providing to the user the at least one relationship recommendation.

Claims

1. A non-transitory computer-readable medium having computer-executable instructions that when executed, causes one or more processors to perform a method for combining data for identifying compatibility, the method comprising:

accessing at least one data source to extract data from said at least one data source that substantially merges all user data;

classifying said data using a classification system;

generating a data vector for said data;

storing said data vector in said classification system;

assessing a user attribute vector to said user data;

comparing said data vector and said user attribute vector to produce at least one relationship recommendation; and

providing to said user said at least one relationship recommendation.

2. The computer-readable medium of claim 1 wherein said classification system has machine learning capabilities including one of emotion detection and personality analysis.

3. The computer-readable medium of claim 1, further providing a positive or negative score for said at least one relationship recommendation based on a relationship matching tool emphasizing a natural relationship.

4. The computer-readable medium of claim 1 wherein social information is comprised within the data in said data source.

5. The computer-readable medium of claim 1 wherein said data source is comprised of unstructured text data.

6. A system for combining data to identify compatibility, having one or more processors being comprised within said system;

means for accessing at least one data source to extract data from said at least one data source that substantially merges all user data;

means for classifying said data using a classification system;

means for generating a data vector for said data;

means for storing said data vector in said classification system;

means for assessing a user attribute vector to said user data;

means for comparing said data vector and said user attribute vector to produce at least one relationship recommendation; and

means for providing to said user said at least one relationship recommendation.

7. The system as in claim 6 wherein said classification system has machine learning capabilities including one of emotion detection and personality analysis.

8. The system as in claim 6 further comprising providing a positive or negative score for said at least one relationship recommendation based on a relationship matching tool emphasizing a natural relationship.

9. The system as in claim 6 wherein social information is comprised within the data in said data source.

10. The system as in claim 6 wherein said data source is comprised of unstructured text data.

11. A system for combining data to identify compatibility,

one or more processors being comprised within said system;

at least one data source having data wherein said data may be extracted therefrom and wherein said data source substantially merges all user data;

a classification system wherein said data may be classified and a data vector generated and stored within said classification system;

a user attribute vector corresponding to said user data; and

at least one relationship recommendation being produced by comparing said data vector and said user attribute vector, said user being provided with said at least one relationship recommendation.

12. The system as in claim 11 wherein said classification system has a machine learning capabilities including one of emotion detection and personality analysis.

13. The system as in claim 11 further providing a positive or negative score for said at least one relationship recommendation based on a relationship matching tool emphasizing a natural relationship.

14. The system as in claim 11 wherein social information is comprised within the data in said data source.

15. The system as in claim 11 wherein said data source is comprised of unstructured text data.