Projections for Efficient Document Clustering

Projections for Efficient Document Clustering (1997)

by Hinrich Schütze , Craig Silverstein

Citations:

86 - 0 self

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Datum	Value	Source
TITLE	Projections for Efficient Document Clustering	user correction - Legacy Corrections
AUTHOR NAME	Hinrich Schütze	user correction
AUTHOR AFFIL	Xerox Palo Alto Research Center	user correction
AUTHOR ADDR	3333 Coyote Hill Road; Palo Alto, CA 94304	user correction
AUTHOR NAME	Craig Silverstein	user correction
AUTHOR AFFIL	Xerox Palo Alto Research Center	user correction
AUTHOR ADDR	3333 Coyote Hill Road; Palo Alto, CA 94304	user correction
ABSTRACT	Clustering is increasing in importance, but linear- and even constant-time clustering algorithms are often too slow for real-time applications. A simple way to speed up clustering is to speed up the distance calculations at the heart of clustering routines. We study two techniques for improving the cost of distance calculations, LSI and truncation, and determine both how much these techniques speed up clustering and how much they affect the quality of the resulting clusters. We find that the speed increase is significant while --- surprisingly --- the quality of clustering is not adversely affected. We conclude that truncation yields clusters as good as those produced by full-profile clustering while offering a significant speed advantage.	user correction
YEAR	1997	INFERENCE
VENUE TYPE	CONFERENCE	INFERENCE
PAGES	74--81	INFERENCE
CITATIONS	29 found	ParsCit 1.0