Social network-based service recommendation with trust enhancement

Shuiguang DENG, Longtao HUANG, Guandong XU

Research output: Contribution to journalArticlespeer-review

167 Citations (Scopus)


Given the increasing applications of service computing and cloud computing, a large number of Web services are deployed on the Internet, triggering the research of Web service recommendation. Despite of service QoS, the use of user feedback is becoming the current trend in service recommendation. Likewise in traditional recommender systems, sparsity, cold-start and trustworthiness are major issues challenging service recommendation in adopting similarity-based approaches. Meanwhile, with the prevalence of social networks, nowadays people become active in interacting with various computers and users, resulting in a huge volume of data available, such as service information, user-service ratings, interaction logs, and user relationships. Therefore, how to incorporate the trust relationship in social networks with user feedback for service recommendation motivates this work. In this paper, we propose a social network-based service recommendation method with trust enhancement known as RelevantTrustWalker. First, a matrix factorization method is utilized to assess the degree of trust between users in social network. Next, an extended random walk algorithm is proposed to obtain recommendation results. To evaluate the accuracy of the algorithm, experiments on a real-world dataset are conducted and experimental results indicate that the quality of the recommendation and the speed of the method are improved compared with existing algorithms.

Original languageEnglish
Pages (from-to)8075-8084
JournalExpert Systems with Applications
Issue number18
Early online dateJul 2014
Publication statusPublished - Dec 2014


Deng, S., Huang, L., & Xu, G. (2014). Social network-based service recommendation with trust enhancement. Expert Systems with Applications, 41(18), 8075-8084.


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