DocumentCode
2699375
Title
Automatic Metadata Generation forWeb Pages Using a Text Mining Approach
Author
Yang, Hsin-Chang ; Lee, Chung-Hong
Author_Institution
Dept. of Electr. Eng., Chang Jung Univ., Tainan
fYear
2005
fDate
8-9 April 2005
Firstpage
186
Lastpage
194
Abstract
The semantic Web has emerged to replace the World Wide Web (WWW or the Web) as the unique platform for information sharing. Applications such as e-commerce will be and could be plausible only if we can annotate the Web pages with their semantics. For newly developed semantic Web resources, such annotation can be done manually or by help of some authoring tools. However, it is not practical to semantically annotating existing Web pages due to the gigantic amount of them. To overcome this difficulty, we propose a machine learning approach to automatically generate semantic metadata for Web pages. The proposed automated process adopts the self-organizing map algorithm to cluster training Web pages and conducts a text mining process to discover some semantic descriptions about the Web pages. Preliminary experiments show that our method may generate semantically relevant metadata for the Web pages
Keywords
Web sites; authoring systems; data mining; learning (artificial intelligence); meta data; self-organising feature maps; semantic Web; text analysis; Web pages; World Wide Web; authoring tools; automatic metadata generation; cluster training; information sharing; machine learning; self-organizing map algorithm; semantic Web resources; semantic descriptions; text mining; Automation; Data mining; Humans; Information management; Machine learning algorithms; Semantic Web; Text mining; Web pages; Web sites; World Wide Web;
fLanguage
English
Publisher
ieee
Conference_Titel
Web Information Retrieval and Integration, 2005. WIRI '05. Proceedings. International Workshop on Challenges in
Conference_Location
Tokyo
Print_ISBN
0-7695-2414-1
Type
conf
DOI
10.1109/WIRI.2005.11
Filename
1553013
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