Cbs Interactive, Inc.

Thomas Osborne

Tushar Pradhan

John F Potter

A dynamic classification dictionary is built for use in profiling and targeting users for additional relevant content. Behavioral data is gathered from user activity, and user documents and actions are categorized. 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 the manner in which 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 into a composite set of taxonomic nouns, and the dynamic classification dictionary is built by storing the composite set of taxonomic nouns.

Personalization engine for building a dynamic classification dictionary

A dynamic classification dictionary is built for use in profiling and targeting users for additional relevant content. Behavioral data is gathered from user activity, and user documents and actions are categorized. 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 the manner in which 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 into a composite set of taxonomic nouns, and the dynamic classification dictionary is build by storing the composite set of taxonomic nouns.

Personalization engine for characterizing a document

Personalization engine for assigning a value index to a user

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.

Personalization engine for classifying unstructured documents

Users of electronic documents are classified for profiling and targeting of additional relevant content. Behavioral data is gathered from user registration information and user activity, and user documents and actions are categorized. Registration information is combined with collaborative and editorial data to provide user profile information. 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 a composite set of taxonomic nouns, and the user is categorized using the taxonomic nouns, and/or the author-generated classification.

Growing community of inventors

San Francisco, CA, United States of America

Thomas Osborne