关键词: Web使用挖掘, 细菌觅食优化, K-means算法, 会话聚类, 电子商务

Abstract: Web user session clustering is an NP-hard problem of the e-commerce field. The purpose is to discover user access patterns of behavior. The difficulty of the problem is that large-scale Web session clustering, and each session is indicated for the high-dimensional vector. This paper presents a type of clustering algorithm combining bacterial foraging algorithm with K-means algorithm, using the well-known data set to test their effectiveness, and the Web session clustering. Compared with the popular clustering algorithm, the experimental results show that the algorithm is efficient and has better performance.

Key words: Web usage mining, bacterial foraging optimization, K-means algorithm, Web session clustering, e-business