Multi-dimensional credibility scoring

• US 8,983,867 B2
• Filed: 03/06/2014
• Issued: 03/17/2015
• Est. Priority Date: 03/14/2013
• Status: Active Grant

• Current Assignee: Dun & Bradstreet Corp., DUN & Bradstreet Incorporated (Dun & Bradstreet Corp.), Hoover's Incorporated (Dun & Bradstreet Holdings, Inc.)
• Original Assignee: Credibility Corp. (Dun & Bradstreet Corp.)
• Inventors: Stibel, Jeffrey M., Lu, Wisdom, Stibel, Aaron B., Hackett, Judith G., Kazerani, Moujan
• Primary Examiner(s): Poinvil, Frantzy
• Application Number:
  US14/199,815
• Publication Number:
  US 20140279394A1
• Time in Patent Office: 376 Days
• Field of Search: 705 1- 44
• US Class Current: 705/38
• CPC Class Codes: G06Q 30/0282 Rating or review of business operators or products
• CPC Class Codes: G06Q 40/03 Credit; Loans; Processing thereof

Abstract

A credibility scoring system produces a multi-dimensional entity credibility score that is derived from multiple dimensional component scores. The credibility scoring system derives each dimensional component score from a different set of credibility data pertaining to different dimensional aspect of overall credibility. The different dimensional aspects factoring into the overall credibility determination include a stability dimension, transparency dimension, trustworthiness dimension, and sentiment dimension.

Claims

1. A computer-implemented method for providing a multi-dimensional presentation of entity credibility, the computer-implemented method comprising:

with a processor of at least one machine of a credibility scoring system comprising a data aggregator, data matcher, and scoring engine;

aggregating from a plurality of data sources to the data aggregator, a plurality of credibility data directed to a particular entity;

grouping, by operation of the data matcher, the plurality of credibility data to at least a first group and a second group, said first group comprising a first subset of the plurality of credibility data that is directed to a first credibility dimension and said second group comprising a second different subset of the plurality of credibility data that is directed to a second different credibility dimension;

computing, by operation of the scoring engine, a first score quantifying the first credibility dimension using the first subset of the credibility data;

computing, by operation of the scoring engine, a second score quantifying the second credibility dimension using the second subset of the credibility data; and

producing, by operation of the scoring engine, an overall credibility score for the particular entity from the first score and the second score.

2. The computer-implemented method of claim 1 further comprising filtering from the plurality of credibility data, (i) credibility data comprising one of sentiment, stability, trust, and transparency indicators as the first subset of credibility data for the first credibility dimension and (ii) credibility data comprising another of the sentiment, stability, trust, and transparency indicators as the second subset of credibility data for the second credibility dimension.

3. The computer-implemented method of claim 1, wherein computing the first score comprises computing a raw score based on the first subset of credibility data and adjusting the raw score according to a distribution to produce the first score, said distribution comprising raw scores of other entities that are computed from other credibility data that is directed to the first credibility dimension.

4. The computer-implemented method of claim 1 further comprising presenting the overall credibility score with the first score and the second score.

5. The computer-implemented method of claim 4 further comprising presenting the first subset of credibility data in connection with presenting the first score and presenting the second subset of credibility data in connection with presenting the second score.

6. The computer-implemented method of claim 4 further comprising producing a report comprising (i) the overall credibility score, (ii) a first credibility dimension comprising the first score and the first subset of credibility data, and (iii) a second credibility dimension comprising the second score and the second subset of credibility data.

7. The computer-implemented method of claim 1, wherein the first subset of the credibility data comprises reviews and ratings that are directed to the particular entity and the second subset of the credibility data comprises historical data about the particular entity.

8. A computer-implemented method for generating a multi-dimensional credibility score, the computer-implemented method comprising:

with a processor of at least one machine of a credibility scoring system comprising a data matcher and scoring engine;

compiling using the data matcher, a first set of credibility data directed to a particular entity and further directed to a first credibility dimension of a plurality of credibility dimensions from any of a plurality of data sources;

compiling using the data matcher, a second set of credibility data directed to the particular entity and further directed to a second credibility dimension of the plurality of credibility dimensions from any of the plurality of data sources;

deriving using the scoring engine, a credibility score for the particular entity from the first and second sets of credibility data; and

presenting from the credibility scoring system, the credibility score in response to an inquiry about the particular entity'"'"'s credibility.

9. The computer-implemented method of claim 8 further comprising aggregating a plurality of credibility data from the plurality of data sources.

10. The computer-implemented method of claim 9, wherein compiling the first set of credibility data comprises filtering the first set of credibility data from the plurality of credibility data, and wherein compiling the second set of credibility data comprises filtering the second set of credibility data from the plurality of credibility data.

11. The computer-implemented method of claim 8, wherein the first set of credibility data comprises reviews and ratings containing sentiment that others have expressed toward the particular entity.

12. The computer-implemented method of claim 11, wherein deriving the credibility score is based in part on a degree of positivity and negativity expressed towards the particular entity in the sentiment from the reviews and ratings of the first set of credibility data.

13. The computer-implemented method of claim 12, wherein the second set of credibility data comprises historical information about the particular entity.

14. The computer-implemented method of claim 13, wherein deriving the credibility score is further based in part on at least one of an amount of historical information about the particular entity that is available and consistency in said historical information.

15. The computer-implemented method of claim 12, wherein the second set of credibility data comprises trust indicators provided by others that attest to the trustworthiness of the particular entity.

16. A non-transitory computer-readable storage medium with an executable program stored thereon, wherein the program instructs a processor of at least one machine of a credibility scoring system comprising a data matcher and scoring engine to perform sets of instructions for:

compiling a first set of credibility data directed to a particular entity and further directed to a first credibility dimension of a plurality of credibility dimensions using the data matcher;

compiling a second set of credibility data directed to the particular entity and further directed to a second credibility dimension of the plurality of credibility dimensions using the data matcher; and

generating using the scoring engine, a credibility report comprising (i) a first section presenting the first credibility dimension with a first score and the first set of credibility data from which the first score is derived, (ii) a second section presenting the second credibility dimension with a second score and the second set of credibility data from which the second score is derived, and (iii) a third section presenting overall credibility of the particular entity as a third score derived in part from the first and second scores.

17. The non-transitory computer-readable storage medium of claim 16, wherein the program further instructs the processor to perform a set of instructions for producing the first score from positive and negative sentiment that is expressed in the first set of credibility data.

18. The non-transitory computer-readable storage medium of claim 16, wherein the first set of credibility data comprises online posts with sentiment directed to the particular entity, and wherein the second set of credibility data comprises information about the particular entity that is aggregated from an online presence of the particular entity.

19. The non-transitory computer-readable storage medium of claim 16, wherein the program further instructs the processor to perform a set of instructions for aggregating from a plurality of data sources, a plurality of credibility data comprising the first and second sets of credibility data and matching the first set of credibility data and the second set of credibility data from the plurality of credibility data to the particular entity.

20. The non-transitory computer-readable storage medium of claim 16, wherein the program further instructs the processor to perform a set of instructions for storing the credibility report to the non-transitory computer-readable storage medium for subsequent retrieval and presentation in response to a query for a credibility report of the particular entity.