Quantifying a Data Source's Reputation

• US 20090125382A1
• Filed: 11/05/2008
• Published: 05/14/2009
• Est. Priority Date: 11/07/2007
• Status: Abandoned Application

• Current Assignee: KPMG LLP (KPMG International Cooperative)
• Original Assignee: Wise Window, Inc.
• Inventors: Delepet, Rajiv
• Application Number:
  US12/265,130
• Publication Number:
  US 20090125382A1
• Time in Patent Office: Days
• US Class Current: 705/10
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 30/0282 Rating or review of business operators or products

Abstract

Methods of quantifying a reputation for a data source are presented. Historical documents having opinions and that are attributed to a data source are identified. The opinions preferably are quantifiable and can be converted into a predication. As the predications are verified, the data source is assigned one or more predication scores indicating the accuracy of the predications. A reputation score for a new document having a new predication can be assigned to the data source as a function of the predictions scores from the historical documents, data source affiliations, document topics, or other parameters. The reputation score relating to the new document can be presented to a user via a computer interface as a single-value, or multiple values corresponding to different topics.

Claims

1. A method of quantifying a reputation of a data source with respect to a topic, the method comprising:

searching for web documents relating to a first topic and attributed to a data source based on a search term;

forming a set of historical documents from the web documents satisfying the search term where each of the historical documents includes an opinion of the data source with respect to the topic;

converting each opinion automatically into a quantifiable predication;

correlating at least some of the quantifiable predictions with verifiable outcomes to derive an outcome score for each of the at least some of the predications;

assigning a prediction score to the data source as a function of the outcome scores;

deriving a reputation score of the data source with respect to a new opinion within a current document from the data source and relating to a second topic as a function of the prediction score; and

presenting the reputation score relating to the current document to a user via a computer interface.

2. The method of claim 1, wherein the step of searching for web documents includes using a publicly available third party search engine.

3. The method of claim 1, wherein the step of deriving the reputation score includes adjusting the reputation score as a function of an affiliation of the data source with an organization.

4. The method of claim 3, wherein the data source is an employee of the organization.

5. The method of claim 3, further comprising adjusting the reputation score as a function of at least two different affiliations of the data source.

6. The method of claim 1, wherein the second topic is different than the first topic.

7. The method of claim 6, wherein the step of deriving the reputation score includes adjusting the reputation score as a function of a similarity measure between the first and the second topic.

8. The method of claim 6, further comprising classifying the historical documents according to subject using subject-based search terms that encompass the first topic and the second topic.

9. The method of claim 8, further comprising calculating the similarity measure based on a hierarchical classification of the first and the second topic.

10. The method of claim 1, wherein the data source comprises a business.

11. The method of claim 1, wherein the data source comprises a person.

12. The method of claim 1, wherein the data source comprises a computer model.

13. The method of claim 1, further comprising updating the predication score upon availability of additional historical documents.

14. The method of claim 13, wherein the additional historical documents include the current document after the new predication has been verified.

15. The method of claim 1, wherein the step of presenting the reputation score along with the current document includes presenting a second reputation score for a second, different data source having a predication on a third topic that is substantially the same as the second topic.

16. The method of claim 1, wherein the quantifiable prediction comprises a discernable time frame.

17. The method of claim 1, wherein the computer interface comprises a web service application program interface.

18. The method of claim 1, wherein the first topic comprises a domain defined by a third party'"'"'s classification scheme.

19. The method of claim 18, wherein the second topic comprises a category within the domain.

20. The method of claim 1, wherein the reputation score comprises multiple values.

21. The method of claim 20, wherein the reputation score includes a measure of precision.

22. The method of claim 20, wherein the reputation score includes a first value for the first topic and a second value for the second topic.