Self-organising maps for hierarchical tree view document clustering using contextual information

Self-organising maps for hierarchical tree view document clustering using contextual information (2002)

by Richard Freeman , Hujun Yin

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Datum	Value	Source
TITLE	Self-organising maps for hierarchical tree view document clustering using contextual information	INFERENCE
AUTHOR NAME	Richard Freeman	user correction
AUTHOR AFFIL	University of Manchester Institute of Science and Technology (UMIST),; Department of Electrical Engineering and Electronics,; PO Box 88	user correction
AUTHOR ADDR	Manchester, M60 1QD,; United Kingdom	user correction
AUTHOR NAME	Hujun Yin	user correction
AUTHOR AFFIL	University of Manchester Institute of Science and Technology (UMIST),; Department of Electrical Engineering and Electronics,; PO Box 88	user correction
AUTHOR ADDR	Manchester, M60 1QD,; United Kingdom	user correction
ABSTRACT	In this paper we propose an effective method to cluster documents into a dynamically built taxonomy of topics, directly extracted from the documents. We take into account short contextual information within the text corpus, which is weighted by importance and used as input to a set of independently spun growing Self-Organising Maps (SOM). This work shows an increase in precision and labelling quality in the hierarchy of topics, using these indexing units. The use of the tree structure over sets of conventional twodimensional maps creates topic hierarchies that are easy to browse and understand, in which the documents are stored based on their content similarity.	user correction - Legacy Corrections
YEAR	2002	INFERENCE
VENUE	PROCEEDINGS OF THE	user correction
VENUE TYPE	CONFERENCE	INFERENCE
CITATIONS	13 found	ParsCit 1.0