Document clustering with K-tree
| Contribuinte(s) |
Geva, S. Kamps, J. Trotman, A. |
|---|---|
| Data(s) |
2009
|
| Resumo |
This paper describes the approach taken to the XML Mining track at INEX 2008 by a group at the Queensland University of Technology. We introduce the K-tree clustering algorithm in an Information Retrieval context by adapting it for document clustering. Many large scale problems exist in document clustering. K-tree scales well with large inputs due to its low complexity. It offers promising results both in terms of efficiency and quality. Document classification was completed using Support Vector Machines. |
| Formato |
application/pdf |
| Identificador | |
| Publicador |
Springer |
| Relação |
http://eprints.qut.edu.au/27756/1/INEX_2008_Paper.pdf DOI:10.1007/978-3-642-03761-0_43 De Vries, Christopher M. & Geva, Shlomo (2009) Document clustering with K-tree. Lecture Notes in Computer Science, 5631/2, pp. 420-431. |
| Direitos |
Copyright 2009 Springer |
| Fonte |
Faculty of Science and Technology |
| Palavras-Chave | #080109 Pattern Recognition and Data Mining #080201 Analysis of Algorithms and Complexity #080704 Information Retrieval and Web Search #INEX #XML Mining #Clustering #K-tree #Tree #Vector Quantization #Text Classification #Support Vector Machine |
| Tipo |
Journal Article |
