Contribution in edited book
Social Tagging Recommender Systems



Publication Details
Authors:
Jäschke, R.; Hotho, A.; Stumme, G.
Editor:
Ricci Francesco, Rokach Lior, Shapira Bracha, Kantor B. Paul
Publisher:
Springer
Place:
New York
Publication year:
2011
Pages range:
615-644
Book title:
Recommender Systems Handbook
ISBN:
978-0-387-85819-7

Abstract
The new generation of Web applications known as (STS) is successfully established and poised for continued growth. STS are open and inherently social; features that have been proven to encourage participation. But while STS bring new opportunities, they revive old problems, such as information overload. Recommender Systems are well known applications for increasing the level of relevant content over the noise that continuously grows as more and more content becomes available online. In STS however, we face new challenges. Users are interested in finding not only content, but also tags and even other users. Moreover, while traditional recommender systems usually operate over 2-way data arrays, STS data is represented as a third-order tensor or a hypergraph with hyperedges denoting (user, resource, tag) triples. In this chapter, we survey the most recent and state-of-the-art work about a whole new generation of recommender systems built to serve STS.We describe (a) novel facets of recommenders for STS, such


Keywords
collaborative, recommender, social, tagging

Last updated on 2019-25-07 at 11:10