A document clustering algorithm for discovering and describing topics
- 1 April 2010
- journal article
- Published by Elsevier BV in Pattern Recognition Letters
- Vol. 31 (6), 502-510
- https://doi.org/10.1016/j.patrec.2009.11.013
Abstract
No abstract availableKeywords
This publication has 10 references indexed in Scilit:
- Text document clustering based on frequent word meaning sequencesData & Knowledge Engineering, 2008
- Topic discovery based on text mining techniquesInformation Processing & Management, 2007
- High Quality, Efficient Hierarchical Document Clustering Using Closed Interesting ItemsetsIEEE International Conference on Data Mining (ICDM), 2006
- Neighbor number, valley seeking and clusteringPattern Recognition Letters, 2006
- Topic themes for multi-document summarizationPublished by Association for Computing Machinery (ACM) ,2005
- Hierarchical Document Clustering Using Frequent ItemsetsPublished by Society for Industrial & Applied Mathematics (SIAM) ,2003
- The automated acquisition of topic signatures for text summarizationPublished by Association for Computational Linguistics (ACL) ,2000
- Scatter/Gather: a cluster-based approach to browsing large document collectionsPublished by Association for Computing Machinery (ACM) ,1992
- SLINK: An optimally efficient algorithm for the single-link cluster methodThe Computer Journal, 1973
- A Nonparametric Estimate of a Multivariate Density FunctionThe Annals of Mathematical Statistics, 1965