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Trust-Based Personalized Service Recommendation: A Network Perspective

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Abstract

Recent years have witnessed a growing trend of Web services on the Internet. There is a great need of effective service recommendation mechanisms. Existing methods mainly focus on the properties of individual Web services (e.g., functional and non-functional properties) but largely ignore users’ views on services, thus failing to provide personalized service recommendations. In this paper, we study the trust relationships between users and Web services using network modeling and analysis techniques. Based on the findings and the service network model we build, we then propose a collaborative filtering algorithm called Trust-Based Service Recommendation (TSR) to provide personalized service recommendations. This systematic approach for service network modeling and analysis can also be used for other service recommendation studies.

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Authors and Affiliations

  1. College of Computer Science and Technology, Zhejiang University, Hangzhou, 310027, China

    Shui-Guang Deng, Long-Tao Huang, Jian Wu & Zhao-Hui Wu

Authors
  1. Shui-Guang Deng
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  2. Long-Tao Huang
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  3. Jian Wu
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  4. Zhao-Hui Wu
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Corresponding author

Correspondence to Jian Wu.

Additional information

This research is supported in part by the National Key Technology Research and Development Program of China under Grant No. 2013BAD19B10, and the National Natural Science Foundation of China under Grant No. 61170033.

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Deng, SG., Huang, LT., Wu, J. et al. Trust-Based Personalized Service Recommendation: A Network Perspective. J. Comput. Sci. Technol. 29, 69–80 (2014). https://doi.org/10.1007/s11390-014-1412-2

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  • DOI: https://doi.org/10.1007/s11390-014-1412-2

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