Topic Based Recommender System & Methods

Abstract

A recommendation system is used to provide suggestions in environments such as message boards, RSS aggregators, blogs and the like by comparing member interests and creating recommendation items corresponding to categorized topics or other members. In some instances a natural language can assist in processing content to sort it into the appropriate topic bin. An advertising module cooperates with the system to provide content based ads relevant to the recommended items.

Description

RELATED APPLICATION DATA[0001]The present application claims the benefit under 35 U.S.C. 119(e) of the priority date of Provisional Application Ser. No. 60 / 826,677 filed Sep. 22, 2006 which is hereby incorporated by reference herein.FIELD OF THE INVENTION[0002]The present invention relates to electronic recommendation systems and other related systems.BACKGROUND[0003]Recommender systems are well known in the art. In one example, such systems can make recommendations for movie titles to a subscriber. In other instances they can provide suggestions for book purchases, or even television program viewing. Such algorithms are commonplace in a number of Internet commerce environments, including at Amazon, CDNOW, and Netflix to name a few, as well as programming guide systems such as TiVO.[0004]Traditionally recommender systems are used in environments in which a content provider is attempting to provide new and interesting material to subscribers, in the form of additional products and se...

AI Technical Summary

Benefits of technology

[0006]An object of the present invention, therefore, is to reduce and / or overcome the aforementioned limitations of the prior art. A recommender system which evaluates multiple data sources is employed to generate more accurate and relevant predictions concerning data items and other users within a community.

Problems solved by technology

Nonetheless the use of recommenders has not been extended fully to such domains and other online areas, including social networks, which could benefit from such systems.

In such systems, however, the extra dimensionality arises from additional content related to items which are nonetheless still traditional commerce items, such as movies.

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