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The Social Network Role in Improving Recommendation Performance of Collaborative Filtering

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Proceedings of the First International Conference on Advanced Data and Information Engineering (DaEng-2013)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 285))

Abstract

Recently a recommender system has been applied to solve several different problems that face the users. Collaborative filtering is the most commonly used and successfully deployed recommendation technique. Despite everything, the traditional collaborative filtering (TCF) operates only in the two-dimensional user-item space. The explosive growth of online social networks in recent times has presented a powerful source of information to be utilised as an extra source for assisting in the recommendation process. The purpose of this paper is to give an overview of collaborative filtering (CF) and existing methods used social network information to incorporate in collaborative filtering recommender systems to improve performance and accuracy. We classify CF-based social network information into two categories: TCF-based trust relation approaches and TCF-based friendship relation approaches. For each category, we review the fundamental concept of methods that can be used to improve recommendation performance.

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Acknowledgments

This work is supported by the Ministry of Higher Education (MOHE) and Research Management Centre (RMC) at the Universiti Teknologi Malaysia (UTM) under Research University Grant Category (VOT Q.J130000.2528.02H99).

Author information

Authors and Affiliations

  1. Faculty of Computing, Universiti Teknologi Malaysia, Skudai, 81310, Johor Bahru, Johor, Malaysia

    Waleed Reafee & Naomie Salim

  2. Faculty of Pure and Applied Science, International University of Africa, 2469, Khartoum, Republic of the Sudan

    Waleed Reafee

Authors
  1. Waleed Reafee
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  2. Naomie Salim
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Corresponding author

Correspondence to Naomie Salim .

Editor information

Editors and Affiliations

  1. Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, Malaysia

    Tutut Herawan

  2. Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Malaysia

    Mustafa Mat Deris

  3. School of Information Technology, Deakin University, Burwood, Victoria, Australia

    Jemal Abawajy

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Reafee, W., Salim, N. (2014). The Social Network Role in Improving Recommendation Performance of Collaborative Filtering. In: Herawan, T., Deris, M., Abawajy, J. (eds) Proceedings of the First International Conference on Advanced Data and Information Engineering (DaEng-2013). Lecture Notes in Electrical Engineering, vol 285. Springer, Singapore. https://doi.org/10.1007/978-981-4585-18-7_27

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  • DOI: https://doi.org/10.1007/978-981-4585-18-7_27

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-4585-17-0

  • Online ISBN: 978-981-4585-18-7

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