You are not logged in.

Integrating instance-level and attribute-level knowledge into document clustering

Wang, Jinlong, Wu, Shunyao, Li, Gang and Wei, Zhe 2011, Integrating instance-level and attribute-level knowledge into document clustering, Computer science and information systems, vol. 8, no. 3, pp. 635-651, doi: 10.2298/CSIS100906003W.

Attached Files
Name Description MIMEType Size Downloads

Title Integrating instance-level and attribute-level knowledge into document clustering
Author(s) Wang, Jinlong
Wu, Shunyao
Li, GangORCID iD for Li, Gang
Wei, Zhe
Journal name Computer science and information systems
Volume number 8
Issue number 3
Start page 635
End page 651
Total pages 17
Publisher Computer Science and Information Systems (COMSIS)
Place of publication Novi Sad, Serbia
Publication date 2011
ISSN 1820-0214
Keyword(s) document clustering
pairwise constraints
Summary In this paper, we present a document clustering framework incorporating instance-level knowledge in the form of pairwise constraints and attribute-level knowledge in the form of keyphrases. Firstly, we initialize weights based on metric learning with pairwise constraints, then simultaneously learn two kinds of knowledge by combining the distance-based and the constraint-based approaches, finally evaluate and select clustering result based on the degree of users’ satisfaction. The experimental results demonstrate the effectiveness and potential of the proposed method.
Language eng
DOI 10.2298/CSIS100906003W
Field of Research 080109 Pattern Recognition and Data Mining
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category C1 Refereed article in a scholarly journal
HERDC collection year 2011
Persistent URL

Document type: Journal Article
Collection: School of Information Technology
Connect to link resolver
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in TR Web of Science
Scopus Citation Count Cited 0 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 279 Abstract Views, 5 File Downloads  -  Detailed Statistics
Created: Mon, 05 Dec 2011, 12:45:39 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact