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Recommender Systems Review of Types, Techniques, and Applications

Recommender Systems Review of Types, Techniques, and Applications
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Author(s): George A. Sielis (University of Cyprus, Cyprus), Aimilia Tzanavari (University of Nicosia, Cyprus & Cyprus University of Technology, Cyprus) and George A. Papadopoulos (University of Cyprus, Cyprus)
Copyright: 2015
Pages: 11
Source title: Encyclopedia of Information Science and Technology, Third Edition
Source Author(s)/Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-4666-5888-2.ch714

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Abstract

Recommender or recommendation systems are software tools that make useful suggestions to users, by taking into account their profile, preferences and/or actions during interaction with an application or website. They are usually personalized and can refer to items to buy, people to connect to or books/ articles to read. Recommender Systems (RS) aim at helping users with their interaction by bringing to surface the information that is relevant to them, their needs, or their tasks. This article's objective is to present a review of the different types of RS, the techniques and methods used for building such systems, the algorithms used to generate the recommendations and how these systems can be evaluated. Finally, a number of topics are discussed as envisioned future research directions.

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