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| QoS prediction for Web services based on hybrid collaborative filtering |
| YU Dong-jin, YIN Yu-yu, WU Meng-meng, LIU Yu |
| School of Computer, Hangzhou Dianzi University, Hangzhou, 310018, China |
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Abstract In order to avoid the unsatisfying results for selection of Web services due to the lack of historical quality of service (QoS) data, a collaborative-filtering-based method was proposed, It predicteds the missing QoS values using different approaches based on the characteristics and the related regional information of the target users and services. For the special users and services, or the region-sensitive services, it employed the user-based or service-based approaches. Otherwise, employed the adjusted Euclidean distance equation for their similarity calculation, and introduced the balance factors to integrate the user-based result and service-based result. The
experimental results based on a real public dataset show that the method achieves the high precision especially for the sparse historical QoS datasets.
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Published: 01 November 2014
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基于混合协同过滤的Web服务QoS预测方法
为了解决由于服务质量（QoS）历史数据缺失而造成基于QoS的Web服务选择无法得到满意结果的问题,提出一种基于混合协同过滤的Web服务质量预测方法.该方法根据目标用户和目标服务自身特性和相关区域信息,选用不同的预测方法计算缺失的QoS值.如用户（或服务）属于特殊用户类（或特殊服务类）,或者服务对区域敏感,则采用基于用户和基于服务的预测方法.否则,利用改进后的欧氏距离测量服务和用户的相似度,并通过引入平衡因子整合基于用户和基于服务的2种不同预测方法.基于真实公开的数据集的实验结果表明,该方法具有较高的Web服务QoS的预测精度,尤其在历史QoS数据稀疏情况下.
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