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State-of-the-Art in Group Recommendation and New Approaches for Automatic Identification of Groups

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Information Retrieval and Mining in Distributed Environments

Part of the book series: Studies in Computational Intelligence ((SCI,volume 324))

Abstract

Recommender systems are important tools that provide information items to users, by adapting to their characteristics and preferences. Usually items are recommended to individuals, but there are contexts in which people operate in groups. To support the recommendation process in social activities, group recommender systems were developed. Since different types of groups exist, group recommendation should adapt to them, managing heterogeneity of groups. This chapter will present a survey of the state-of-the-art in group recommendation, focusing on the type of group each system aims to. A new approach for group recommendation is also presented, able to adapt to technological constraints (e.g., bandwidth limitations), by automatically identifying groups of users with similar interests.

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Authors and Affiliations

  1. Dipartimento di Matematica e Informatica, Università di Cagliari, Via Ospedale 72, 09124, Cagliari, Italy

    Ludovico Boratto & Salvatore Carta

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  1. Ludovico Boratto
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  2. Salvatore Carta
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Editors and Affiliations

  1. Parco Scientifico della Sardegna, CRS4, Center of Advanced Studies Research and Development in Sardinia, Ed. 1 09010 Loc. Piscinamanna, Pula, CA, Italy

    Alessandro Soro  & Gavino Paddeu  & 

  2. Department of Electrical and Electronic Engineering, University of Cagliari, Piazza d’Armi, 09123, Cagliari, Italy

    Eloisa Vargiu  & Giuliano Armano  & 

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Boratto, L., Carta, S. (2010). State-of-the-Art in Group Recommendation and New Approaches for Automatic Identification of Groups. In: Soro, A., Vargiu, E., Armano, G., Paddeu, G. (eds) Information Retrieval and Mining in Distributed Environments. Studies in Computational Intelligence, vol 324. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16089-9_1

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  • DOI: https://doi.org/10.1007/978-3-642-16089-9_1

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