Method of testing online recommender system

a recommendation system and online technology, applied in the field of testing, evaluating and measuring the performance of electronic recommendation systems, can solve the problems of not being completely neutral in cf algorithms, affecting the reliability and reputation of recommender systems, and not being able to recommend items, so as to improve online advertising campaigns
US20140100950A1Inactive Publication Date: 2014-04-10GROSS JOHN NICHOLAS
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Patent Information

Authority / Receiving Office
US · United States
Patent Type
Applications(United States)
Current Assignee / Owner
GROSS JOHN NICHOLAS
Publication Date
2014-04-10
Estimated Expiration
Not applicable · inactive patent

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Abstract

A recommender system can be analyzed to determine various performance characteristics of an online content service provider. The recommender system is analyzed using a predetermined policy, to determine if it satisfies such policy, and / or has other measurable intended and / or unintended biases. The policy can include such parameters as whether a particular profile is presented with certain particular types of items by the recommender system. The reliability of search engines can also be tested using a similar approach.
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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 performance of electronic recommendation 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. While the details of such algorithms are often proprietary, the latter typically use a number of parameters for determining a user's movie “tastes” so to speak, including demographics, pr...

Claims

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