PERSONALIZATION ENGINE FOR CLASSIFYING UNSTRUCTURED DOCUMENTS

• US 20090327243A1
• Filed: 01/30/2009
• Published: 12/31/2009
• Est. Priority Date: 06/27/2008
• Status: Active Grant

• Current Assignee: CBS Interactive Inc. (ViacomCBS Incorporated)
• Original Assignee: CBS Interactive Inc. (ViacomCBS Incorporated)
• Inventors: Pradhan, Tushar, Osborne, Thomas, Potter, John
• Granted Patent: US 8,214,346 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 16/335 Filtering based on additional data, e.g. user or group profiles filtering in web context G06F16/9535, G06F16/9536
• CPC Class Codes: G06F 16/353 into predefined classes
• CPC Class Codes: G06F 16/93 Document management systems
• CPC Class Codes: G06F 16/958 Organisation or management of web site content, e.g. publishing, maintaining pages or automatic linking

Abstract

Unstructured electronic documents are classified for profiling and targeting users for additional relevant content. Behavioral data is gathered from user activity, and user documents and actions are categorized. Profile information is combined with collaborative and editorial data to provide users with credible information regarding products. Author-generated document classification information is analyzed and assigned a first taxonomic noun to characterize the document. User-generated tags characterizing a portion of the document are assigned a second taxonomic noun. Search terms that resulted in the user accessing the document are identified and assigned a third taxonomic noun. Attributes related to how the document was accessed are evaluated and assigned a fourth taxonomic noun. The document is processed using pattern rules to extract a fifth taxonomic noun. The taxonomic nouns are aggregated to determine term vectors representing the document, and the document is categorized using the term vectors, the taxonomic nouns, or the author-generated classification.

Claims

1. A computer-implemented method for classifying an electronic document, the method comprising:

analyzing author-generated classification information regarding the document with a document classification server and assigning a set of first taxonomic nouns to characterize the document based upon the author-generated classification information;

examining a user-generated tag from a client computer characterizing a portion of the document and assigning a set of second taxonomic nouns to characterize the document based upon the user-generated tag characterization;

identifying a search term that resulted in the user accessing the document from a content provider site server and assigning at set of third taxonomic nouns to characterize the document based upon the search term result;

evaluating attributes related to the manner in which a user accesses the document from the content provider site server and assigning a set of fourth taxonomic nouns to characterize the document based upon the attributes related to the manner in which the document was accessed;

processing the document with a content analysis server to extract a set of fifth taxonomic nouns to characterize the document based upon a predetermined pattern rule;

aggregating the taxonomic nouns with a personalization engine server to determine term vectors that represent the document; and

categorizing the document based upon at least one of the term vectors, the taxonomic nouns, and the author-generated classification scheme with a targeting server.

2. The computer-implemented method for classifying an electronic document of claim 1, wherein the author-generated information includes an author classification of the document characterizing a portion of the document.

3. The computer-implemented method for classifying an electronic document of claim 1, wherein the author-generated information includes metadata assigned to the document.

4. The computer-implemented method for classifying an electronic document of claim 1, wherein the user-generated tag characterizing a portion of the document includes at least one of an item listed in a profile of the user and a technology implementation setting.

5. The computer-implemented method for classifying an electronic document of claim 1, wherein the attributes related to the manner in which the user accessed the document include at least one of a network type used to access the document, a Web site from which the document was accessed, an electronic correspondence to which the document was associated, a time of day the document was accessed, a referrer who directed the user to the document, and a document category used by a repository storing the document to describe the document.

6. The computer-implemented method for classifying an electronic document of claim 1, wherein the attributes related to the manner in which the user accessed the document include a click rate indicating a level of a user'"'"'s relative interest in the document in relation to other documents available to the user.

7. The computer-implemented method for classifying an electronic document of claim 1, wherein processing the document includes weighting the taxonomic nouns using a predetermined weighting scheme.

8. The computer-implemented method for classifying an electronic document of claim 1, wherein determining term vectors includes building a list and a count of taxonomic nouns.

9. The computer-implemented method for classifying an electronic document of claim 8, wherein determining the term vectors includes applying a dictionary of taxonomic nouns with a dictionary building server.

10. The computer-implemented method for classifying an electronic document of claim 9, wherein the list of taxonomic nouns includes a document and occurrence count.

11. The computer-implemented method for classifying an electronic document of claim 10 further comprising:

updating the dictionary database of known taxonomic nouns from the list of taxonomic nouns to further identify taxonomic nouns in additional documents.

12. The computer-implemented method for classifying an electronic document of claim 1, wherein categorizing the electronic document based upon the term vectors includes processing the term vectors to derive a topic set.

13. The computer-implemented method for classifying an electronic document of claim 12, wherein categorizing the electronic document based upon the term vectors further includes computing a similarity measure between the electronic document and the topic set.

14. The computer-implemented method for classifying an electronic document of claim 12, wherein categorizing the electronic document based upon the term vectors further includes executing a self search to identify additional taxonomic nouns to create an additional topic set.

15. The computer-implemented method for classifying an electronic document of claim 12, wherein categorizing the electronic document based upon the term vectors further includes executing a co-occurrence analysis to identify and cluster related taxonomic nouns to create a taxonomic noun cluster.

16. The computer-implemented method for classifying an electronic document of claim 15 further comprising:

editing at least one of the taxonomic noun cluster, a topic set, a term vector, and a taxonomic noun.

17. The computer-implemented method for classifying an electronic document of claim 1, wherein processing the document with the content analysis server to extract a set of fifth taxonomic nouns includes:

electronically reading the text of the document;

breaking the electronically read text into a series of words and punctuation characters;

comparing sequences of consecutive words with known terms read from an electronic dictionary database to determine if a match exists;

merging the matching consecutive words into a single multi-word term if a match exists and, if a match does not exist, assigning a single word term;

processing the multi-word term against a set of pattern rules with a pattern rules server to identify a part of speech assignment and a term type assignment; and

combining the terms and the part of speech assignment and the term type assignment into a structured term vector.

18. A computer-implemented method for classifying an electronic document, the method comprising:

determining term vectors that represent the document based upon taxonomic nouns, the taxonomic nouns being prepared by one or more of the following steps;

analyzing author-generated classification information regarding the document with a document classification server and assigning a set of first taxonomic nouns to characterize the document based upon the author-generated classification information;

examining a user-generated tag from a client computer characterizing a portion of the document and assigning a set of second taxonomic nouns to characterize the document based upon the user-generated tag characterization;

identifying a search term that resulted in the user accessing the document from a content provider site server and assigning a set of third taxonomic nouns to characterize the document based upon the search term result;

evaluating attributes related to the manner in which a user accesses the document from the content provider site server and assigning a set of fourth taxonomic nouns to characterize the document based upon the attributes related to the manner in which the document was accessed; and

processing the document with a content analysis server to extract a set of fifth taxonomic nouns to characterize the document based upon a predetermined pattern rule; and

categorizing the document based upon at least one of the term vectors, the taxonomic nouns, and the author-generated classification information.

19. A system for classifying an electronic document, the system comprising:

a document classification server configured for analyzing author-generated classification information regarding the document and assigning a set of first taxonomic nouns to characterize the document based upon the author-generated classification information;

a content analysis server configured for examining a user-generated tag characterizing a portion of the document and assigning a set of second taxonomic nouns to characterize the document based upon the user-generated tag characterization;

a profiling server configured for identifying a search term that resulted in the user accessing the document and assigning at set of third taxonomic nouns to characterize the document based upon the search term result and further configured for evaluating attributes related to the manner in which a user accesses the document and assigning a set of fourth taxonomic nouns to characterize the document based upon the attributes related to the manner in which the document was accessed;

wherein the content analysis server is further configured for processing the document to extract a set of fifth taxonomic nouns to characterize the document based upon a predetermined pattern rule; and

a personalization server configured for aggregating the taxonomic nouns to determine term vectors that represent the document and for categorizing the document based upon at least one of the term vectors, the taxonomic nouns, and the author-generated classification scheme.

20. A computer program product with instructions recorded thereon for classifying an electronic document, the computer program product comprising:

instructions for analyzing author-generated classification information regarding the document with a document classification server and assigning a set of first taxonomic nouns to characterize the document based upon the author-generated classification information;

instructions for examining a user-generated tag from a client computer characterizing a portion of the document and assigning a set of second taxonomic nouns to characterize the document based upon the user-generated tag characterization;

instructions for identifying a search term that resulted in the user accessing the document from a content provider site server and assigning at set of third taxonomic nouns to characterize the document based upon the search term result;

instructions for evaluating attributes related to the manner in which a user accesses the document from the content provider site server and assigning a set of fourth taxonomic nouns to characterize the document based upon the attributes related to the manner in which the document was accessed;

instructions for processing the document with a content analysis server to extract a set of fifth taxonomic nouns to characterize the document based upon a predetermined pattern rule;

instructions for aggregating the taxonomic nouns with a personalization engine server to determine term vectors that represent the document; and

instructions for categorizing the document based upon at least one of the term vectors, the taxonomic nouns, and the author-generated classification scheme with a targeting server.