Method of evaluating learning rate of recommender systems

a recommendation system and learning rate technology, applied in the field of evaluating the learning rate of recommender systems, can solve the problems of not being completely neutral in the recommendation algorithm, affecting the reliability and reputation of the recommendation system, and not being able to recommend items, etc., and achieve the effect of improving online advertising campaigns
US20100312613A1Inactive Publication Date: 2010-12-09JOHN NICHOLAS & KRISTIN GROSS
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Patent Information

Authority / Receiving Office
US · United States
Patent Type
Applications(United States)
Current Assignee / Owner
JOHN NICHOLAS & KRISTIN GROSS
Publication Date
2010-12-09
Estimated Expiration
Not applicable · inactive patent

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Abstract

A recommender system is analyzed to determine various performance characteristics, such as a learning rate for new items, or a learning rate for new subscriber tastes. Comparisons of different recommenders are presented to assist consumers and marketers in selecting appropriate e-commerce sites for purchasing, advertising, etc.
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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 / 473,994 filed May 28, 2003, which is hereby incorporated by reference.FIELD OF THE INVENTION

[0002] The present invention relates to testing, evaluating and measuring learning rates and other performances of electronic recommendation systems and other related systems employed by online content service providers.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. While the details of such algorithms are often proprietary, the latter typically use a num...

Claims

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