2011Unpublished venueRequires access

Social recommender systems

Ido Guy, David Carmel

Open publisher page 99 citations

Abstract

The goal of this tutorial is to expose participants to the current research on social recommender systems (i.e., recommender systems for the social web). Participants will become familiar with state-of-the-art recommendation methods, their classifications according to various criteria, common evaluation methodologies, and potential applications that can utilize social recommender systems. Additionally, open issues and challenges in the field will be discussed.

About this research paper

What this paper is about

The goal of this tutorial is to expose participants to the current research on social recommender systems (i.e., recommender systems for the social web). Participants will become familiar with state-of-the-art recommendation methods, their classifications according to various criteria, common evaluation methodologies, and potential applications that can utilize social recommender systems. Additionally, open issues and challenges in the field will be discussed.

Why it matters

OpenAlex reports 99 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

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Method / approach

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Main findings

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Limitations

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Applications

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Available abstract

The goal of this tutorial is to expose participants to the current research on social recommender systems (i.e., recommender systems for the social web). Participants will become familiar with state-of-the-art recommendation methods, their classifications according to various criteria, common evaluation methodologies, and potential applications that can utilize social recommender systems. Additionally, open issues and challenges in the field will be discussed.

Key concepts: Recommender system, Computer science, Field (mathematics), Social web, World Wide Web, Social media, Data science, Pure mathematics

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