基于孟然论潜在语义分析的Web使用挖掘

Web使用挖掘的首要任务是发现Web用户访问行为的模式.传统聚类算法对解空间的搜索带有盲目性和缺乏语义特征.提出了一种基于盖然论潜在语义分析(PLSA)的发现和分析Web访问模式的方法,即通过定量地衡量出Web用户和Web对象与潜在因素之间的概率关系,再利用盖然论的方法来完成各种分析任务.实验结果表明该方法具有高效性.

Web Usage Mining Based on Probabilistic Latent Semantic Analysis

The primary goal of Web usage mining is the discovery of patterns in the navigational behavior of Web users. But the classical algorithms of clustering are aimless in searching the solution space and absent of semantic characters.The paper provides a method of discovery and analysis of Web navigational patterns based on PLSA.Quantitatively measuring the relationships between Web users and hidden factors,as well as between Web objects and hidden factors in terms of probabilities,a variety of analysis tasks can be performed by using probabilistic inference.Experimental results show that this method has good effectiveness.