Recommender Systems and the Social Web.pdf

Recommender Systems and the Social Web

Fatih Gedikli

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 users 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.

PDF-Ebook: There is an increasing demand for recommender systems due to the information overload users are facing on the Web. The goal of a recommender Recent developments have brought a new source for bootstrapping recommender systems: social web services. The variety of social web services, each with its ...

2.26 MB DATEIGRÖSSE
9783658019488 ISBN
Englisch SPRACHE
Recommender Systems and the Social Web.pdf

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Sofia Voigt

recommender systems for ltering the abundant information. Extensive research for rec-ommender systems is conducted by a broad range of communities including social and computer scientists, physicists, and interdisciplinary researchers. Despite substantial theo-retical and practical achievements, uni cation and comparison of di erent approaches are

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Matteo Müller

Recommender systems can be theroughcategory into three main types: collaborative filtering recommender system, content-based recommender system, and. recommendation in web logs and similar social networks. First, we present a collaborative recommendation using the link structure of a social network and ...

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Noel Schulze

Download [PDF] Recommender Systems And The …

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Jason Lehmann

Recent developments have brought a new source for bootstrapping recommender systems: social web services. The variety of social web services, each with its ...

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Jessica Kohmann

Abstract—In this paper we propose a concept of a web e-com- merce system that collects and uses, in the process of making recommendations, data obtained ... In recent years the demand of social networking websites has been increased due to frequent uses of these sites by people. Social Networks play important role  ...