Abstract
Web services are ever increasingly published on the network as core components of Service-oriented architecture (SOA). An attendant problem is how to help users select their satisfied services that meet their functional and non-functional requirements from the mass services. Service recommendation technology is adopted and studied as an effective approach currently. This paper focuses on the user’s trust network, where the users share their experience and rating for the invoked services. To attack the data sparsity and cold-start problems in the user-service rating matrix, an improved random walk algorithm is proposed. Firstly, we employ the non-negative matrix factorization method to compute the similarities between users and services separately. Then our method introduces the trust relationship in iterations of the random walk to select the trust users accurately. At last, the real dataset is used to validate our approach. Experimental results show the effectiveness of our approach compared with the state-of-art algorithms.
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WebserviceX.Net: http://www.webservicex.net/ws/default.aspx.
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Acknowledgments
This work was funded by the Natural Science Foundation of Shandong Province (NSFS Grant No. ZR2014FL013) and the Independent Innovation and Achievements Transformation Special Project of Shandong Province (No. 2014ZZCX02702). The authors acknowledge the support of the Opening Fund of Shandong Provincial Key Laboratory for Network Based Intelligent Computing.
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Li, G., Zheng, Z., Wang, H., Yang, Z., Xu, Z., Liu, L. (2017). A Novel Service Recommendation Approach Considering the User’s Trust Network. In: Wang, S., Zhou, A. (eds) Collaborate Computing: Networking, Applications and Worksharing. CollaborateCom 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 201. Springer, Cham. https://doi.org/10.1007/978-3-319-59288-6_39
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DOI: https://doi.org/10.1007/978-3-319-59288-6_39
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