社会化标注中用户动态标签云构建研究

Constructing Dynamic Social Tag Cloud for User Interests

【目的】标签云可用于信息检索推荐和导航,由于用户标注具有时序特征,为有效揭示用户兴趣动态变化,提出基于时序演化的用户动态标签云构建方法。【方法】利用心理学中记忆的遗忘和加强特征构建标签的动态权重,从而建立用户动态标签云以反映用户关注点的变化。【结果】与现有的标签云算法比较,构建的用户动态标签云算法能够根据用户动态变化的兴趣有效地对标签进行排序,在用户兴趣标签的预测效果上明显高于其他算法,并具有更高的推荐准确率。【局限】因为用户兴趣在短时间周期内不会有太大变化,动态的方法在短时间周期内的预测效果不是很显著,但在长时间周期表现上更为显著。【结论】基于时序演化的用户动态标签云能有效地把握用户当前的兴趣热点,提高个性化检索和导航的效果。

[Objective] Social tags can be used for the recommendation and navigation sections of information retrieval systems. This paper proposes a method to construct a dynamic user tag cloud based on the temporal evolution to reveal the changes of user interests. [Methods] We established the tags＇ dynamic weights with the forgetting and strengthening characteristics of memory in psychology. Thus, the dynamic user tag cloud reflect user＇s changing focus. [Results] Compared with the existing ones, the proposed algorithm could effectively sort the tags, and then make accurate predictions or recommendations. [Limitations] The proposed method performed well over long period of time because user＇s interests do not change significantly in a short period of time. [Conclusions] The proposed algorithm could effectively identify user＇s interests and then improve the personalized services.