People engine optimization

• US 8,468,028 B2
• Filed: 01/08/2013
• Issued: 06/18/2013
• Est. Priority Date: 06/01/2011
• 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., Stibel, Aaron B.
• Primary Examiner(s): OUELLETTE, JONATHAN P
• Application Number:
  US13/736,276
• Publication Number:
  US 20130124540A1
• Time in Patent Office: 161 Days
• Field of Search: None
• US Class Current: 705/1.1
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 16/9538 Presentation of query results
• CPC Class Codes: G06F 16/957 Browsing optimisation, e.g. caching or content distillation
• CPC Class Codes: G06Q 30/018 Certifying business or products

Abstract

Some embodiments promote website credibility and the optimization of websites for people by automatedly quantifying various elements of a website into component credibility scores. In some embodiments, a set of encoded credibility scoring rules are used to compute each of the component credibility scores, wherein the credibility scoring rules are derived based on factors that have been identified by a grouping of people that preferably represent a primary demographic of users that consume the content of a particular classified type of website. In some such embodiments, the credibility scoring rules are derived from commonality that is identified from a sample set of known credible and/or non-credible websites of a particular classification. Once the credibility scoring rules are defined, the system applies the rules to other websites having the same classification as those from which the rules are derived to automatically generate credibility scores for the other websites.

Claims

1. For a website optimization system comprising at least one server with at least one processor and non-transitory computer-readable memory, a computer-implemented method for automatically assessing whether visual elements of a website increase or decrease the website'"'"'s credibility, the computer-implemented method comprising:

classifying by operation of the processor, each website of a plurality of websites based on subject matter of the website;

identifying by operation of the processor, a group of credible websites from a set of the plurality of websites that are similarly classified, wherein each website of the group of credible websites is composed of a different set of visual elements defining a presentation for the website in a browser;

determining by operation of the processor, a common set of visual elements presented in each credible website of the group of credible websites;

scanning by operation of the processor, visual elements present on a new website that is not in the group of credible websites and that is similarly classified as the group of credible websites;

computing by operation of the processor, a credibility score for the new website based on comparison of a particular visual element that is present on the new website and that is also present in the common set of visual elements; and

presenting from the website optimization system, the credibility score in conjunction with presentation of the particular visual element of the new website.

2. The computer-implemented method of claim 1 further comprising encoding a set of credibility scoring rules from the common set of visual elements, each credibility scoring rule providing a first score connoting an increase in credibility for a visual element that is shared by a threshold number of credible websites in the group of credible websites and providing a second score connoting a decrease in credibility for a visual element that is not present in any credible website of the group of the credible websites.

3. The computer-implemented method of claim 2 further comprising identifying the particular visual element on the new website from said scanning.

4. The computer-implemented method of claim 3 further comprising applying a credibility scoring rule from the set of credibility scoring rules that quantifies credibility of the particular visual element, said credibility scoring rule producing the credibility score for the particular visual element based on similarity between the particular visual element of the new website and the particular visual element of each credible website.

5. The computer-implemented method of claim 1 further comprising increasing the credibility score based on each additional credible website of the group of credible websites presenting the particular visual element.

6. The computer-implemented method of claim 1 further comprising increasing the credibility score when an attribute defined for the particular visual element of the new website is defined for the particular visual element of a threshold number of the credible websites.

7. The computer-implemented method of claim 6 further comprising decreasing the credibility score when an attribute defined for the particular visual element of the new website is not defined for the particular visual element of any credible website of the group of credible websites.

8. The computer-implemented method of claim 1, wherein identifying the group of credible websites comprises identifying a set of the plurality of websites that are similarly classified and that exceed a popularity threshold based on a number of visitors to each website.

9. The computer-implemented method of claim 1, wherein identifying the group of credible websites comprises (i) aggregating reviews targeting each website of the plurality of websites from at least one social media site and (ii) identifying a set of the plurality of websites that are similarly classified with reviews exceeding a specified threshold.

10. The computer-implemented method of claim 1, wherein computing the credibility score comprises providing a high credibility score for a visual element resembling the particular visual element and a low credibility score for a visual element differing from the particular visual element.

11. For a system comprising at least one server with a processor and non-transitory computer-readable memory, a computer-implemented method for automatically assessing website credibility, the computer-implemented method comprising:

classifying by operation of the processor, each website of a plurality of websites based on subject matter of the website;

identifying by operation of the processor, a group of credible websites from a set of similarly classified websites;

detecting by operation of the processor, a common set of visual elements presented in the group of credible websites;

determining by operation of the processor, a range of attributes defined by the group of credible websites for presentation of a particular visual element of the common set of visual elements;

defining by operation of the processor, a credibility scoring rule quantifying credibility attributed to the particular visual element based on usage of the range of attributes by the group of credible web sites;

identifying by operation of the processor, an attribute defined for the particular visual element of a similarly classified particular website that is not in the group of credible websites; and

computing by operation of the processor, a credibility score for the particular visual element of the particular website according to the credibility scoring rule, the credibility score rule outputting a first score connoting increased credibility when the attribute for the particular visual element of the particular website matches an attribute specified for the particular visual element by a threshold number of credible websites from the group of credible websites and produces a second score connoting decreased credibility when the attribute for the particular visual element of the particular website is not an attribute specified for the particular visual element by any credible website of the group of credible websites.

12. The computer-implemented method of claim 11, wherein defining the credibility scoring rule comprises defining increasing scores for attributes in the range of attributes that are specified for the particular visual element by a greater number of the credible websites.

13. The computer-implemented method of claim 11 further comprising presenting the particular website with the credibility score adjacent to the particular visual element.

14. The computer-implemented method of claim 11 further comprising determining a plurality of visual elements presented on the particular website by downloading and parsing the particular website.

15. The computer-implemented method of claim 11 further comprising obtaining the attribute that is specified for the particular visual element of the particular website by parsing code for rendering the particular website.

16. A computer-implemented method performed by a credibility scoring system comprising at least one server device with a processor, the computer-implemented method for assessing credibility of a website, the computer-implemented method comprising:

identifying by operation of the processor, a definition that is specified for each visual element of a set of visual elements of a particular website;

tracking by operation of the processor, different definitions that are specified for each visual element of a set of visual elements that are common across a set of credible websites, wherein the set of credible websites and the particular website relate to common subject matter;

computing by operation of the processor, a credibility score for each visual element of the particular website based on proximity of the definition for each visual element of the particular element to the definitions of a corresponding visual element specified by the set of credible websites; and

presenting from the credibility scoring system, credibility of the particular website by rendering the particular website and presenting a credibility score adjacent to each visual element of the set of visual elements of the particular website, each credibility score quantifying an impact that a particular visual element has on overall credibility of the particular website.

17. The computer-implemented method of claim 16 further comprising determining the set of credible websites from a plurality of websites reciting subject matter similar to that of the particular website based on popularity of the set of credible websites relative to the plurality of websites.

18. The computer-implemented method of claim 16 further comprising computing an overall credibility score for the particular website based in part on the credibility scores computed for each visual element of the set of visual elements of the particular website.

19. The computer-implemented method of claim 17 further comprising presenting the overall credibility score in conjunction with presenting the credibility of the particular website.

20. The computer-implemented method of claim 16, wherein computing a credibility score for a particular visual element comprises specifying a first value when the definition for the particular visual element of the particular website does not correspond to any definition specified for a corresponding particular visual element of the set of credible websites and specifying a second value when the definition for the particular visual element of the particular website corresponds to a definition specified by at least one credible website of the plurality of websites for the corresponding particular visual element, and wherein the second value is greater than the first value.