Abstract
Both the functional properties and the non-functional properties (known as quality of service, QoS) should be considered when recommending services. In mobile environment, the services are referred to under different contexts. Context-aware collaborative filtering is often employed to predict the QoS of candidate services when a user submits a service request. Existing collaborative filtering based methods seldom analyze the actual impact of each context property on the QoS properties in context-similarity mining. To address the problem, we propose a QoS prediction method based on the context-QoS association mining in this paper. The method is composed of two steps. We firstly propose an algorithm to mine the association between the context and the QoS properties. Then, a QoS prediction approach is proposed by taking the association and the context similarity into consideration. To study the effectiveness of our approach, we experiment on real world dataset. Experimental results show that our proposed method can improve the accuracy of QoS prediction.
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Acknowledgment
This work was supported by Science and Technology on Information Transmission and Dissemination in Communication Networks Laboratory. The research was supported by NSFC (61571066).
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© 2017 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Hu, Y., Sun, Q., Li, J. (2017). QoS Prediction Based on Context-QoS Association Mining. 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_29
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DOI: https://doi.org/10.1007/978-3-319-59288-6_29
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