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Recent Advances of Neural Network Models and Applications pp 215–222Cite as

A Collaborative Filtering Recommender Exploiting a SOM Network

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Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 26))

Abstract

Recommender systems are exploited in many fields for helping users to find goods and services. A collaborative filtering recommender realizes a knowledge-sharing system to find people having similar interests. However, some critical issues may lead to inaccurate suggestions. To provide a solution to such problems, this paper presents a novel SOM-based collaborative filtering recommender. Some experimental results confirm the effectiveness of the proposed solution.

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Author information

Authors and Affiliations

  1. DICEAM, University “Mediterranea” of Reggio, Calabria Loc. Feo di Vito, 89122, Reggio Calabria, Italy

    Giuseppe M. L. Sarnè

Authors
  1. Giuseppe M. L. Sarnè
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Correspondence to Giuseppe M. L. Sarnè .

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Milano, Milano, Italy

    Simone Bassis

  2. Department of Psychology, Second University of Naples, Institute for Advanced Scientific Studies (IIASS), Caserta, Italy

    Anna Esposito

  3. Department of Civil, Energy, Environmental, and Materials Engineering, DICEAM, University Mediterranea of Reggio Calabria, Reggio Calabria, Italy

    Francesco Carlo Morabito

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Sarnè, G.M.L. (2014). A Collaborative Filtering Recommender Exploiting a SOM Network. In: Bassis, S., Esposito, A., Morabito, F. (eds) Recent Advances of Neural Network Models and Applications. Smart Innovation, Systems and Technologies, vol 26. Springer, Cham. https://doi.org/10.1007/978-3-319-04129-2_21

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  • DOI: https://doi.org/10.1007/978-3-319-04129-2_21

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-04128-5

  • Online ISBN: 978-3-319-04129-2

  • eBook Packages: EngineeringEngineering (R0)

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