Abstract: A system and method for performing classification using semantic distance measurements. Items of electronic content accessed by individuals over a global communications network are identified. A set of content that includes the plurality of identified items of electronic content are stored. The set of content is normalized. Each of the keywords contained the set of content is identified and a semantic distance between each of the identified keywords is measured.

Abstract: A content classification system, method and computer product is presented. In connection with the invention, a data structure is created by identifying a plurality of words and mapping each word to one or more categories. The data structure is indexed. An item of content is identified and classified based on the data structure. The classification includes identifying all one—or more—word combinations in the item of content; for each word of at least a pre-determined number of characters in length in each of the word combinations, identifying each of the categories to which it is mapped; and determining a weight for each of the words based on an inverse proportion to the number of categories to which it is mapped.

Abstract: A plurality of pages viewed by a communications network user (e.g., an Internet user) are classified as pertaining to one of a plurality of topics. A count of each of the pages viewed by the communications network user for each of the topics is tracked, as is a recency with which each of the pages viewed by the communications network user was viewed for each of the topics. The communications network user is characterized as belonging to one or more behavioral segments based on the count and the recency. Advertisements are served to the communications network user based on at least advertising targeting parameters and the characterization.

Abstract: A plurality of pages viewed by a communications network user (e.g., an Internet user) are classified as pertaining to one of a plurality of topics. A count of each of the pages viewed by the communications network user for each of the topics is tracked, as is a recency with which each of the pages viewed by the communications network user was viewed for each of the topics. The communications network user is characterized as belonging to one or more behavioral segments based on the count and the recency. Advertisements are served to the communications network user based on at least advertising targeting parameters and the characterization.

Abstract: A system and method for performing classification using semantic distance measurements. Items of electronic content accessed by individuals over a global communications network are identified. A set of content that includes the plurality of identified items of electronic content are stored. The set of content is normalized. Each of the keywords contained the set of content is identified and a semantic distance between each of the identified keywords is measured.

Abstract: A content classification system, method and computer product is presented. In connection with the invention, a data structure is created by identifying a plurality of words and mapping each word to one or more categories. The data structure is indexed. An item of content is identified and classified based on the data structure. The classification includes identifying all one—or more—word combinations in the item of content; for each word of at least a pre-determined number of characters in length in each of the word combinations, identifying each of the categories to which it is mapped; and determining a weight for each of the words based on an inverse proportion to the number of categories to which it is mapped.