With the rapid development of information technology, the significance of clustering in the process of delivering information to users is becoming more eminent. Especially in the web information space, clustering analysis can prove particularly beneficial for a variety of applications such as web personalisation and profiling, caching and prefetching and content delivery networks. In this paper, we propose a bi-clustering approach, which identifies groups of related web users and pages. The proposed approach is a three-step process that relies on the principles of spectral clustering analysis and provides a fuzzy relation scheme for the revealed users' and pages' clusters. Experiments have been conducted on both synthetic and real datasets to prove the proposed method's efficiency and reveal hidden knowledge.
Koutsonikola, V.A. et al. REF proposed a bi-clustering approach for web data, which identifies groups of related web users and pages using spectral clustering method on both row and column dimensions.
A fuzzy bi-clustering approach to correlate web users and pages
I. J. Knowledge and Web Intelligence
I. J. Knowledge and Web Intelligence
Computer Science