基于数据挖掘的可视化数字图书馆用户社区聚类与特征分析

Data Mining-Based User Community Clustering and Character Analyzing in Visualized Digital Library

提出了基于Web数据挖掘技术的用户社区聚类方法和相关量化技术。实际应用表明该方法能够有效的分析用户特征,从而提高数字图书馆的服务质量和水平。另一个方面,由于可视化建模技术的应用使得在用户信息分析过程中的直观性和科学性更加突出,给数据分析提供了有效的手段。

In this paper, we proposed a mechanism to implement the user communities clustering which is based on web data mining techniques. The practice proved this mechanism can effectively analyze the users＇ characteristic which can improve the service quality of the current digital library. On the other hand, the process of analyzing users＇ information becomes more intuitive and scientific thanks to the visualized modeling technique which provide an effective method to data analyze.