DocumentCode
1175618
Title
Guest Editors´ Introduction: Mining Actionable Knowledge on the Web
Author
Yang, Qiang ; Knoblock, Craig A. ; Wu, Xindong
Volume
19
Issue
6
fYear
2004
Firstpage
30
Lastpage
31
Abstract
The Web-its resources and users-offers a wealth of information for data mining and knowledge discovery. Up to now, a great deal of work has been done applying data mining and machine learning methods to discover novel and useful knowledge on the Web. However, many techniques aim only at extracting knowledge for human users to view and use. Recently, more and more work addresses Web for knowledge that computer systems will use. You can apply such actionable knowledge back to the Web for measurable performance improvements. This special issue of IEEE Intelligent Systems features five articles that address the problem of actionable Web mining.
Keywords
World Wide Web; actionable knowledge; collaborative filtering; content-based image retrieval; crawler; data mining; information extraction; Clustering algorithms; Collaboration; Crawlers; Data mining; Filtering algorithms; Humans; Information filtering; Information filters; Web mining; Web pages; World Wide Web; actionable knowledge; collaborative filtering; content-based image retrieval; crawler; data mining; information extraction;
fLanguage
English
Journal_Title
Intelligent Systems, IEEE
Publisher
ieee
ISSN
1541-1672
Type
jour
DOI
10.1109/MIS.2004.64
Filename
1363731
Link To Document