Topic Based Recommender System & Methods

a recommendation system and recommendation technology, applied in the field of electronic recommendation systems, can solve the problems of additional content related to items, the use of recommenders has not been fully extended to such domains and other online areas,

Inactive Publication Date: 2008-03-27
JOHN NICHOLAS & KRISTIN GROSS
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

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.

Method used

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  • Topic Based Recommender System & Methods
  • Topic Based Recommender System & Methods

Examples

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Embodiment Construction

[0008]FIG. 1 illustrates an example of a preferred embodiment of a multi-dimensional recommender system 100. A user / item compiler and database 110 includes a schema in which ratings for individual items by individual users are identified in a typical matrix fashion well-known in the art. The primary difference, in this instance, is that the items are not products / services (i.e., books, movies, etc.) as in the prior art, but instead represent more generalized concepts, such as a rating identified by a user for an author, a social network contact, a particular message board or post, a particular blog or website, a particular RSS Feed, etc., as shown by the data received from sources.

Explicit Endorsement Data Sources 120

[0009]As an example of an explicit data source 120, in a typical message board application such as operated by Yahoo! (under the moniker Yahoo Message Boards) or the Motley Fool, users are permitted to designate “favorite” authors, and / or to “recommend” posts written by...

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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...

Claims

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Application Information

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IPC IPC(8): G06F17/30G06Q30/00
CPCG06F17/30699G06Q30/02G06Q30/0273G06Q30/0256G06F17/3053G06Q30/0255G06Q50/01G06F17/30867G06F17/3097G06Q30/0269G06F16/90324G06F16/335G06F16/9535G06F16/24578
Inventor GROSS, JOHN NICHOLAS
Owner JOHN NICHOLAS & KRISTIN GROSS
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