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Context-Aware Collaborative Prediction

  • Shu Wu
  • Qiang Liu
  • Liang Wang
  • Tieniu Tan

Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)

Table of contents

  1. Front Matter
    Pages i-xi
  2. Shu Wu, Qiang Liu, Liang Wang, Tieniu Tan
    Pages 1-5
  3. Shu Wu, Qiang Liu, Liang Wang, Tieniu Tan
    Pages 7-17
  4. Shu Wu, Qiang Liu, Liang Wang, Tieniu Tan
    Pages 19-29
  5. Shu Wu, Qiang Liu, Liang Wang, Tieniu Tan
    Pages 31-41
  6. Shu Wu, Qiang Liu, Liang Wang, Tieniu Tan
    Pages 43-51
  7. Shu Wu, Qiang Liu, Liang Wang, Tieniu Tan
    Pages 53-69

About this book

Introduction

This book presents two collaborative prediction approaches based on contextual representation and hierarchical representation, and their applications including context-aware recommendation, latent collaborative retrieval and click-through rate prediction. The proposed techniques offer significant improvements over current methods, the key determinants being the incorporated contextual representation and hierarchical representation. To provide a background to the core ideas presented, it offers an overview of contextual modeling and the theory of contextual representation and hierarchical representation, which are constructed for the joint interaction of entities and contextual information.

The book offers a rich blend of theory and practice, making it a valuable resource for students, researchers and practitioners who need to construct systems of information retrieval, data mining and recommendation systems with contextual information.

Keywords

Collaborative prediction Hierarchical representation Contextual representation Contextual information Context-aware Contextual operation

Authors and affiliations

  • Shu Wu
    • 1
  • Qiang Liu
    • 2
  • Liang Wang
    • 3
  • Tieniu Tan
    • 4
  1. 1.National Laboratory of Pattern RecognitionInstitute of Automation, Chinese Academy of SciencesBeijingChina
  2. 2.National Laboratory of Pattern RecognitionInstitute of Automation, Chinese Academy of SciencesBeijingChina
  3. 3.National Laboratory of Pattern RecognitionInstitute of Automation, Chinese Academy of SciencesBeijingChina
  4. 4.National Laboratory of Pattern Recognition, Institute of AutomationChinese Academy of SciencesBeijingChina

Bibliographic information

  • DOI https://doi.org/10.1007/978-981-10-5373-3
  • Copyright Information The Author(s) 2017
  • Publisher Name Springer, Singapore
  • eBook Packages Computer Science
  • Print ISBN 978-981-10-5372-6
  • Online ISBN 978-981-10-5373-3
  • Series Print ISSN 2191-5768
  • Series Online ISSN 2191-5776
  • Buy this book on publisher's site
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