融合社交行为和社会化标签的移动情境感知服务研究

Mobile Context-aware Service Combining Social Behavior and Social Tags

[目的/意义]为了提高移动情境感知的服务质量,文章构建了融合社交行为和社会化标签的移动情境感知服务模型。[方法/过程]首先利用子空间聚类算法对标签进行聚类,再计算融入时间因子的用户—标签偏爱度,然后计算基于社交行为影响下的用户相似度,最后将两者进行结合,通过调和权重得到融合社交行为和社会化标签的用户—资源预测评分。[结果/结论]通过MovieLens数据集的实验结果表明,融合社交行为和社会化标签的移动情境感知服务模型可以有效提高推荐系统的准确率和召回率。[局限]实验论证部分没有对社交行为和社会化标签的主次影响进行进一步的有效论证说明。

[Purpose/significance]This paper constructs a mobile context-aware service model which combines social behavior and social tags,which can improve the service quality of mobile context awareness.[Method/process]First,the paper uses subspace clustering algorithm to cluster the tags,then calculates the user-tags preference with time factor and the users’similarity based on social behavior,finally combines the two factors to obtain the user-resources prediction score integrating social behavior and social tags through reconciling weights.[Result/conclusion]The experimental results of MovieLens data set show that the precision and recall of the mobile context-aware service system combining social behavior and social tags are improved significantly.[Limitations]The experiment does not further demonstrate the rank of impacts of social behavior and social tags.