[Objective] To solve the problem that recommender systems recommend outdated information resources to the target user. [Methods] This paper proposes an individual recommendation method for information resource based on dynamic tag resources network graph. Firstly, resource network graph is established to form resource semantic relationships, using common tags in two resource objects as a link pairwise. Secondly, tag network graph with time is created to describe users' interest drifting using the links in resource network graph. Thirdly, top N information resource objects are recommended to target user from tag network graph by matching target users' dynamic tags describing users' interest drifting. [Results] In MovieLens data set, the experimental results show that this information recommendation method can trace and predict users' interest drifting, and recommend accurate resource to users. Mean Absolute Error (MAE) is lower than the traditional methods by about 15%. [Limitations] The method does not involve the problem that information resources are recommended under real-time dynamic environment such as information retrieval with users' interests drifting rapidly. [Conclusions] The proposed method can recommend more accurate information resource to users with interest drifting.
王忠群, 蒋胜, 修宇, 皇苏斌, 汪千松. 基于动态标签-资源网络图的信息资源推荐[J]. 现代图书情报技术, 2015, 31(3): 49-57.
Wang Zhongqun, Jiang Sheng, Xiu Yu, Huang Subin, Wang Qiansong. Information Resource Recommendation Method Based on Dynamic Tag-Resource Network. New Technology of Library and Information Service, 2015, 31(3): 49-57.
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