SpringerBriefs in Electrical and Computer Engineering

Trust for Intelligent Recommendation

Authors: Bhuiyan, Touhid

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  • ISBN 978-1-4614-6895-0
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Softcover $39.95
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About this book

Recommender systems are one of the recent inventions to deal with the ever-growing information overload in relation to the selection of goods and services in a global economy. Collaborative Filtering (CF) is one of the most popular techniques in recommender systems. The CF recommends items to a target user based on the preferences of a set of similar users known as the neighbors, generated from a database made up of the preferences of past users. In the absence of these ratings, trust between the users could be used to choose the neighbor for recommendation making. Better recommendations can be achieved using an inferred trust network which mimics the real world “friend of a friend” recommendations. To extend the boundaries of the neighbor, an effective trust inference technique is required.

This book proposes a trust interference technique called Directed Series Parallel Graph (DSPG) that has empirically outperformed other popular trust inference algorithms, such as TidalTrust and MoleTrust. For times when reliable explicit trust data is not available, this book outlines a new method called SimTrust for developing trust networks based on a user’s interest similarity. To identify the interest similarity, a user’s personalized tagging information is used. However, particular emphasis is given in what resources the user chooses to tag, rather than the text of the tag applied. The commonalities of the resources being tagged by the users can be used to form the neighbors used in the automated recommender system. Through a series of case studies and empirical results, this book highlights the effectiveness of this tag-similarity based method over the traditional collaborative filtering approach, which typically uses rating data.

Trust for Intelligent Recommendation is intended for practitioners as a reference guide for developing improved, trust-based recommender systems. Researchers in a related field will also find this book valuable.

Table of contents (7 chapters)

  • Introduction

    Bhuiyan, Touhid

    Pages 1-8

  • Literature Review

    Bhuiyan, Touhid

    Pages 9-32

  • Trust Inferences Using Subjective Logic

    Bhuiyan, Touhid

    Pages 33-51

  • Online Survey on Trust and Interest Similarity

    Bhuiyan, Touhid

    Pages 53-61

  • SimTrust: The Algorithm for Similarity-Based Trust Network Generation

    Bhuiyan, Touhid

    Pages 63-73

Buy this book

eBook $29.99
price for USA (gross)
  • ISBN 978-1-4614-6895-0
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $39.95
price for USA
  • ISBN 978-1-4614-6894-3
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Trust for Intelligent Recommendation
Authors
Series Title
SpringerBriefs in Electrical and Computer Engineering
Copyright
2013
Publisher
Springer-Verlag New York
Copyright Holder
The Author(s)
eBook ISBN
978-1-4614-6895-0
DOI
10.1007/978-1-4614-6895-0
Softcover ISBN
978-1-4614-6894-3
Series ISSN
2191-8112
Edition Number
1
Number of Pages
XIV, 119
Number of Illustrations and Tables
34 b/w illustrations
Topics