System and method for the dynamic generation of correlation scores between arbitrary objects

• US 8,200,677 B2
• Filed: 11/09/2010
• Issued: 06/12/2012
• Est. Priority Date: 03/06/2006
• Status: Active Grant

• Current Assignee: Aggregate Knowledge Incorporated (Neustar Incorporated)
• Original Assignee: Aggregate Knowledge Incorporated (Neustar Incorporated)
• Inventors: Martino, Paul, Musumeci, Gian-Paolo, Wehner, Kristopher C.
• Primary Examiner(s): Corrielus, Jean M
• Application Number:
  US12/942,213
• Publication Number:
  US 20110055226A1
• Time in Patent Office: 581 Days
• Field of Search: 707/999.003, 707/999.103, 707/749, 709/206
• US Class Current: 707/749
• CPC Class Codes: G06F 16/337 Profile generation, learning or modification
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: Y10S 707/99933 Query processing, i.e. searching
• CPC Class Codes: Y10S 707/99944 Object-oriented database structure

Abstract

Systems and methods are described for performing the dynamic generation of correlation scores between arbitrary objects. When a behavioral event is recorded, that is to say when an end user interacts with multiple objects, relationships between objects are created. These relationships are maintained as a list. When a request for correlated items is requested based upon a seed object, a list of correlated items is dynamically created through the generation of a pivot set and a scoring algorithm to compute the list of correlated items.

Claims

1. A method of generating a correlation score between arbitrary objects, comprising:

generating a seed object;

retrieving a list of objects corresponding to the seed object from a storage table;

restricting the list of objects based upon a parameter list to generate a pivot set of objects;

generating a candidate set by determining objects that have interacted with each of the pivot set of objects;

computing a score for each member of the candidate set; and

generating a list of correlated items based upon at least one score.

2. The method of claim 1, further comprising:

receiving an external request for recommended content prior to generating the seed object; and

retrieving a list of objects related to the content.

3. The method of claim 1, wherein the seed object is generated via user interaction with the object.

4. The method of claim 1, wherein generating the list of correlated items comprises sorting the score for each member using a pre-established criteria.

5. The method of claim 1, wherein the score is calculated using a vector cosine algorithm.

6. The method of claim 1, wherein the score is calculated using a Pearson'"'"'s R algorithm.

7. The article of manufacture of claim 1, wherein the data, when accessed, results in a machine performing further operations comprising:

receiving an external request for recommended content prior to generating the seed object; and

retrieving a list of objects related to the content.

8. The article of manufacture of claim 1, wherein the seed object is generated via user interaction with the object.

9. The article of manufacture of claim 1, wherein generating the list of correlated items comprises sorting the score for each member using a pre-established criteria.

10. The article of manufacture of claim 1, wherein the score is calculated using a vector cosine algorithm.

11. The article of manufacture of claim 1, wherein the score is calculated using a Pearson'"'"'s R algorithm.