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Recommender Systems for Social Tagging Systems

Part of the SpringerBriefs in Electrical and Computer Engineering Book Series

DOI: 10.1007/978-1-4614-1894-8

ISBN: 978-1-4614-1893-1

Publisher: Springer US - Springer Journals

Jan 24, 2012

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Social Tagging Systems

Marinho, Leandro Balby; Hotho, Andreas; Jäschke, Robert; Nanopoulos, Alexandros; Rendle, Steffen; Schmidt-Thieme, Lars; Stumme, Gerd; Symeonidis, Panagiotis

Pages: 3 –15

[Social Tagging Systems (STS for short) are web applications where users can upload, tag, and share resources (e. g., websites, videos,photos, etc.) with other users. STS promote decentralization of content control and lead the web to be a more open and democratic environment. As we will see in...
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Recommender Systems

Marinho, Leandro Balby; Hotho, Andreas; Jäschke, Robert; Nanopoulos, Alexandros; Rendle, Steffen; Schmidt-Thieme, Lars; Stumme, Gerd; Symeonidis, Panagiotis

Pages: 17 –29

[In the following we will describe systematically and formally the most important problems related to recommender systems and give some references to actual solutions. Our focus here is to describe the general recommender systems setting as a base for social recommender systems. See [11, 3] for a...
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Baseline Techniques

Marinho, Leandro Balby; Hotho, Andreas; Jäschke, Robert; Nanopoulos, Alexandros; Rendle, Steffen; Schmidt-Thieme, Lars; Stumme, Gerd; Symeonidis, Panagiotis

Pages: 33 –42

[In this chapter we introduce the most basic techniques for recommendations in STS. Despite their simplicity, these methods are very easy to implement, cheap to compute, and have proven to attain reasonably good results; features that make them good alternatives to start with by anyone planning...
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Advanced Techniques

Marinho, Leandro Balby; Hotho, Andreas; Jäschke, Robert; Nanopoulos, Alexandros; Rendle, Steffen; Schmidt-Thieme, Lars; Stumme, Gerd; Symeonidis, Panagiotis

Pages: 43 –74

[In this chapter we describe the state-of-the-art in social tagging recommender systems. Many of the algorithms presented here borrow ideas and techniques from other areas such as information retrieval, machine learning, and statistical relational learning. In Section 4.3 we also describe many...
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Offline Evaluation

Marinho, Leandro Balby; Hotho, Andreas; Jäschke, Robert; Nanopoulos, Alexandros; Rendle, Steffen; Schmidt-Thieme, Lars; Stumme, Gerd; Symeonidis, Panagiotis

Pages: 75 –80

[In this chapter we present the most usual experimental protocols and metrics employed for offline evaluation of tag recommender systems. By offline we mean that the algorithms are evaluated on a snapshot of some real-world STS dataset, which, in turn, is typically split into training and test...
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Real World Social Tagging Recommender Systems

Marinho, Leandro Balby; Hotho, Andreas; Jäschke, Robert; Nanopoulos, Alexandros; Rendle, Steffen; Schmidt-Thieme, Lars; Stumme, Gerd; Symeonidis, Panagiotis

Pages: 83 –95

[As an exemplary implementation of a recommender system for social tagging systems we present in this chapter the tag recommendation framework of BibSonomy. It allows to test, evaluate and compare different tag recommendation algorithms in an online setting, where the users of BibSonomy actually...
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Online Evaluation

Marinho, Leandro Balby; Hotho, Andreas; Jäschke, Robert; Nanopoulos, Alexandros; Rendle, Steffen; Schmidt-Thieme, Lars; Stumme, Gerd; Symeonidis, Panagiotis

Pages: 97 –108

[The multiplexing tag recommender of BibSonomy allows for comparisons of different tag recommenders in a realistic real-life setting. We show in this chapter, which kind of evaluation the framework allows and how recommenders perform in practice. We begin with an introduction of the evaluation...
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Conclusions

Marinho, Leandro Balby; Hotho, Andreas; Jäschke, Robert; Nanopoulos, Alexandros; Rendle, Steffen; Schmidt-Thieme, Lars; Stumme, Gerd; Symeonidis, Panagiotis

Pages: 109 –111

[In this chapter we close the book with a summary, a discussion, and future research directions.]

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