Use this url to cite publication: https://hdl.handle.net/20.500.12259/40999
Empirical study on unsupervised feature selection for document clustering
Type of publication
Straipsnis konferencijos medžiagoje Web of Science duomenų bazėje / Article in conference proceedings in Web of Science database (P1a1)
Author(s)
| Author | Affiliation | |
|---|---|---|
LT | ||
Baltijos pažangių technologijų institutas | LT |
Title
Empirical study on unsupervised feature selection for document clustering
Part Of
Human language technologies - the Baltic perspective : proceedings of the 6th international conference, Baltic HLT 2014
Date Issued
| Date |
|---|
2014 |
Publisher
Amsterdam : IOS Press
Publisher (trusted)
Is Referenced by
Extent
p. 107-110
Abstract (en)
Unsupervised feature selection is very important in the document clustering process. This paper presents the empirical research on feature selection as well as clustering methods and feature representation suitability for Lithuanian and Russian document clustering.
Series/Report no.
(Frontiers in artificial intelligence and applications. Vol. 268 0922-6389)
Type of document
type::text::journal::journal article::research article
Language
Anglų / English (en)
Coverage Spatial
Nyderlandai / Netherlands (NL)
ISBN (of the container)
9781614994411
ISSN (of the container)
0922-6389
WOS
WOS:000349540000016
Other Identifier(s)
VDU02-000016080
| Journal | Cite Score | SNIP | SJR | Year | Quartile |
|---|---|---|---|---|---|
Frontiers in Artificial Intelligence and Applications | 0.7 | 0.573 | 0.228 | 2014 | Q4 |