Recommender Systems and the Social Web: Leveraging Tagging Data for Recommender Systems

✍ Scribed by Fatih Gedikli (auth.)

Publisher: Vieweg+Teubner Verlag
Year: 2013
Tongue: English
Leaves: 118
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

There is an increasing demand for recommender systems due to the information overload users are facing on the Web. The goal of a recommender system is to provide personalized recommendations of products or services to users. With the advent of the Social Web, user-generated content has enriched the social dimension of the Web. As user-provided content data also tells us something about the user, one can learn the user’s individual preferences from the Social Web. This opens up completely new opportunities and challenges for recommender systems research. Fatih Gedikli deals with the question of how user-provided tagging data can be used to build better recommender systems. A tag recommender algorithm is proposed which recommends tags for users to annotate their favorite online resources. The author also proposes algorithms which exploit the user-provided tagging data and produce more accurate recommendations. On the basis of this idea, he shows how tags can be used to explain to the user the automatically generated recommendations in a clear and intuitively understandable form. With his book, Fatih Gedikli gives us an outlook on the next generation of recommendation systems in the Social Web sphere.

✦ Table of Contents

Front Matter....Pages i-xi
Introduction....Pages 1-6
Preliminaries....Pages 7-32
LocalRank – A graph-based tag recommender....Pages 33-42
Improving recommendation accuracy based on item-specific tag preferences....Pages 43-55
Evaluation of explanation interfaces in the form of tag clouds....Pages 57-68
An analysis of the effects of using different explanation styles....Pages 69-87
Summary and perspectives....Pages 89-92
Back Matter....Pages 93-112

✦ Subjects

Data Mining and Knowledge Discovery; Information Storage and Retrieval; User Interfaces and Human Computer Interaction

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