Title: Document clustering via adaptive subspace iteration
Abstract:Document clustering has long been an important problem in information retrieval. In this paper, we present a new clustering algorithm ASI1 , which uses explicitly modeling of the subspace structure as...Document clustering has long been an important problem in information retrieval. In this paper, we present a new clustering algorithm ASI1 , which uses explicitly modeling of the subspace structure associated with each cluster. ASI simultaneously performs data reduction and subspace identification via an iterative alternating optimization procedure. Motivated from the optimization procedure, we then provide a novel method to determine the number of clusters. We also discuss the connections of ASI with various existential clustering approaches. Finally, extensive experimental results on real data sets show the effectiveness of ASI algorithm.Read More
Publication Year: 2004
Publication Date: 2004-07-25
Language: en
Type: article
Indexed In: ['crossref']
Access and Citation
Cited By Count: 120
AI Researcher Chatbot
Get quick answers to your questions about the article from our AI researcher chatbot