A visual mining system for theme development evolution analysis of scientific literature

Wang, Jinlong, Wen, Can, Wu, Shunyao and Vu, Huy Quan 2010, A visual mining system for theme development evolution analysis of scientific literature, International journal of digital content technology and its applications JDCTA, vol. 4, no. 3, pp. 215-223.

Attached Files
Name Description MIMEType Size Downloads

Title A visual mining system for theme development evolution analysis of scientific literature
Author(s) Wang, Jinlong
Wen, Can
Wu, Shunyao
Vu, Huy Quan
Journal name International journal of digital content technology and its applications JDCTA
Volume number 4
Issue number 3
Start page 215
End page 223
Total pages 9
Publisher Advanced Institute of Convergence IT (AICIT)
Place of publication Korea
Publication date 2010-06
ISSN 1975-9339
Keyword(s) clustering
text mining
literature
dynamic
Summary Theme development evolution analysis of literature is a significant tool to help the scientific scholars find and study the frontier problems more efficiently. This paper designs and develops a visual mining system for theme development evolution analysis to deal with the large number of literature information. The analysis of related themes based on sub-themes, together with the dynamic threshold strategy are adopted for improving the accuracy of system. Experiments results prove that correlations of themes obtained from the system are accurate and achieve better practical effect in comparison with that of our early work.
Language eng
Field of Research 080109 Pattern Recognition and Data Mining
Socio Economic Objective 810107 National Security
HERDC Research category C1 Refereed article in a scholarly journal
HERDC collection year 2010
Copyright notice ©2010, Advanced Institute of Convergence IT (AICIT). All rights reserved.
Persistent URL http://hdl.handle.net/10536/DRO/DU:30034428

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.

Versions
Version Filter Type
Access Statistics: 209 Abstract Views, 15 File Downloads  -  Detailed Statistics
Created: Fri, 29 Apr 2011, 13:49:45 EST by Sandra Dunoon

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 drosupport@deakin.edu.au.