| Trust-Based Personalized Service Recommendation: A Network Perspective简 |
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| 引用本文： | 邓水光,黄龙涛,吴健,吴朝晖.Trust-Based Personalized Service Recommendation: A Network Perspective简[J].计算机科学技术学报,2014,29(1):69-80. |
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| 作者姓名： | 邓水光 黄龙涛 吴健 吴朝晖 |
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| 作者单位： | College of Computer Science and Technology, Zhejiang University, Hangzhou 31002~ China |
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| 基金项目： | 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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| 摘 要： | Recent years have witnessed a growing trend of Web services on the Interact. There is a great need of effective service recommendation mechanisms. Existing methods mainly focus on the properties of individual Web services （e.g., func- tional 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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| 关 键 词： | personalized service recommendation，trust， network modeling and analysis， collaborative filtering |
Trust-Based Personalized Service Recommendation: A Network Perspective |
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| Shui-Guang Deng,Long-Tao Huang,Jian Wu,Zhao-Hui Wu.Trust-Based Personalized Service Recommendation: A Network Perspective[J].Journal of Computer Science and Technology,2014,29(1):69-80. |
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| Authors: | Shui-Guang Deng Long-Tao Huang Jian Wu Zhao-Hui Wu |
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| Affiliation: | 1. College of Computer Science and Technology, Zhejiang University, Hangzhou, 310027, China
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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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