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An Asymmetric Weighting Schema for Collaborative Filtering

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New Trends in Computational Collective Intelligence

Part of the book series: Studies in Computational Intelligence ((SCI,volume 572))

Abstract

Several key applications like recommender systems need to determine the similarities between users or items. These similarities play an important role in many tasks, such as discovering users with common interests or items with common properties. Most of the traditional methods are symmetric which means that they always assign equal similarity to each user even when one user rating profile is completely like the other but not conversely. In this paper we combine the traditional methods with an asymmetric weighting schema to distinguish between the similarities of two users. Several experiments have been performed to compare the performance of proposed method with traditional similarity measures.

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Correspondence to Parivash Pirasteh .

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Pirasteh, P., Jung, J.J., Hwang, D. (2015). An Asymmetric Weighting Schema for Collaborative Filtering. In: Camacho, D., Kim, SW., Trawiński, B. (eds) New Trends in Computational Collective Intelligence. Studies in Computational Intelligence, vol 572. Springer, Cham. https://doi.org/10.1007/978-3-319-10774-5_7

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  • DOI: https://doi.org/10.1007/978-3-319-10774-5_7

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10773-8

  • Online ISBN: 978-3-319-10774-5

  • eBook Packages: EngineeringEngineering (R0)

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