一种时区聚类协同过滤的空间信息服务质量预测A timezone clustering based collaborative filtering approach for QoGIS prediction
游兰,张海兵,桂志鹏,胡凯,吴华意
摘要(Abstract)：
针对现有研究较少关注时空特征对服务质量的影响,预测准确性有限的不足,该文提出了一种基于时区聚类协同过滤的空间信息服务质量预测算法:利用时区特征进行用户和空间信息服务的聚类,并采用时区优化的相似度计算方法寻找相似用户和相似服务,通过构建时区约束的邻近用户—服务矩阵进行空间信息服务质量的综合预测。最后,实验结果证明基于时区聚类协同过滤方法可以显著提高空间信息服务质量预测的准确性。
关键词(KeyWords)： 空间信息服务质量;协同过滤;空间服务预测;时区
基金项目(Foundation): 国家自然科学基金项目(41371372,41401464)
作者(Author): 游兰,张海兵,桂志鹏,胡凯,吴华意
DOI: 10.16251/j.cnki.1009-2307.2015.05.022
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