METHOD AND APPARATUS FOR RATING DOCUMENTS AND AUTHORS

• US 20130166282A1
• Filed: 12/21/2012
• Published: 06/27/2013
• Est. Priority Date: 12/21/2011
• Status: Abandoned Application

• Current Assignee: Federated Media Publishing LLC (Nexstar Media Group, Inc.)
• Original Assignee: Federated Media Publishing LLC (Nexstar Media Group, Inc.)
• Inventors: Ridge, Peter, Musgrove, Tim
• Application Number:
  US13/725,503
• Publication Number:
  US 20130166282A1
• Time in Patent Office: Days
• US Class Current: 704/9
• CPC Class Codes: G06F 40/30 Semantic analysis

Abstract

Methods and apparatus for determining a competence rating of an author relating to one or more topics is disclosed. An exemplary method comprises determining semantic information associated with one or more documents related to the one or more topics, determining amplification information associated with the one or more documents, determining occurrence information associated with the author; and determining a competence rating for the author based at least in part on the semantic information associated with the one or more documents, the amplification information associated with the one or more documents, and the occurrence information associated with the author. A document rating for at least one of the one or more documents may also be determined based at least in part on the one or more weighted semantic features and the amplification information.

Claims

1. A computer-implemented method executed by one or more computing devices for determining a competence rating of an author relating to one or more topics, the method comprising:

determining, by at least one of the one or more computing devices, semantic information associated with one or more documents related to the one or more topics;

determining, by at least one of the one or more computing devices, amplification information associated with the one or more documents;

determining, by at least one of the one or more computing devices, occurrence information associated with the author; and

determining, by at least one of the one or more computing devices, a competence rating for the author based at least in part on the semantic information associated with the one or more documents, the amplification information associated with the one or more documents, and the occurrence information associated with the author.

2. The method of claim 1, wherein the semantic information relates to at least one of reading level, grammatical correctness, average sentence length and range of vocabulary, topic density, number, density and class of references, presence of argumentation indicators, dialog indicators, first person narrative or authoritative verbiage, the presence of various surface representations of sub-topics or related topics to the one or more topics, and semantics of comments associated with the one or more documents.

3. The method of claim 1, wherein the semantic information is based at least in part on one or more weighted semantic features.

4. The method of claim 3, further comprising determining a document rating for at least one of the one or more documents based at least in part on the one or more weighted semantic features and the amplification information.

5. The method of claim 1, wherein the amplification information is based at least in part on where the one or more documents are published.

6. The method of claim 1, wherein the occurrence information is based on at least one of the number of documents the author has written related to the one or more topics, how recently the author has written documents related to the one or more topics, and how frequently the author has written documents related to the one or more topics.

7. The method of claim 1, wherein the one or more documents include at least one of an existing document and a new document.

8. An apparatus for determining a competence rating of an author relating to one or more topics, the apparatus comprising:

one or more processors; and

one or more memories operatively coupled to at least one of the one or more processors and having instructions stored thereon that, when executed by at least one of the one or more processors, cause at least one of the one or more processors to;

determine semantic information associated with one or more documents related to the one or more topics;

determine amplification information associated with the one or more documents;

determine occurrence information associated with the author; and

determine a competence rating for the author based at least in part on the semantic information associated with the one or more documents, the amplification information associated with the one or more documents, and the occurrence information associated with the author.

9. The apparatus of claim 8, wherein the semantic information relates to at least one of reading level, grammatical correctness, average sentence length and range of vocabulary, topic density, number, density and class of references, presence of argumentation indicators, dialog indicators, first person narrative or authoritative verbiage, the presence of various surface representations of sub-topics or related topics to the one or more topics, and semantics of comments associated with the one or more documents.

10. The apparatus of claim 8, wherein the semantic information is based at least in part on one or more weighted semantic features.

11. The apparatus of claim 10, wherein at least one of the one or more memories has further instructions stored thereon that, when executed by at least one of the one or more processors, cause at least one of the one or more processors to determine a document rating for at least one of the one or more documents based at least in part on the one or more weighted semantic features and the amplification information.

12. The apparatus of claim 8, wherein the amplification information is based at least in part on where the one or more documents are published.

13. The apparatus of claim 8, wherein the occurrence information is based on at least one of the number of documents the author has written related to the one or more topics, how recently the author has written documents related to the one or more topics, and how frequently the author has written documents related to the one or more topics.

14. The apparatus of claim 8, wherein the one or more documents include at least one of an existing document and a new document.

15. At least one non-transitory computer-readable medium storing computer-readable instructions that, when executed by one or more computing devices, cause at least one of the one or more computing devices to:

determine semantic information associated with one or more documents related to the one or more topics;

determine amplification information associated with the one or more documents;

determine occurrence information associated with the author; and

determine a competence rating for the author based at least in part on the semantic information associated with the one or more documents, the amplification information associated with the one or more documents, and the occurrence information associated with the author.

16. The at least one non-transitory computer-readable medium of claim 15, wherein the semantic information relates to at least one of reading level, grammatical correctness, average sentence length and range of vocabulary, topic density, number, density and class of references, presence of argumentation indicators, dialog indicators, first person narrative or authoritative verbiage, the presence of various surface representations of sub-topics or related topics to the one or more topics, and semantics of comments associated with the one or more documents.

17. The at least one non-transitory computer-readable medium of claim 15, wherein the semantic information is based at least in part on one or more weighted semantic features.

18. The at least one non-transitory computer-readable medium of claim 17, further comprising instructions that, when executed by one or more computing devices, cause at least one of the one or more computing devices to determine a document rating for at least one of the one or more documents based at least in part on the one or more weighted semantic features and the amplification information.

19. The at least one non-transitory computer-readable medium of claim 15, wherein the amplification information is based at least in part on where the one or more documents are published.

20. The at least one non-transitory computer-readable medium of claim 15, wherein the occurrence information is based on at least one of the number of documents the author has written related to the one or more topics, how recently the author has written documents related to the one or more topics, and how frequently the author has written documents related to the one or more topics.

21. The at least one non-transitory computer-readable medium of claim 15, wherein the one or more documents include at least one of an existing document and a new document.