On web communities mining and analysis

Zhang, Y; Xu, G

On web communities mining and analysis

Zhang, Y Xu, G

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Publication Type:: Conference Proceeding
Citation:: 3rd International Conference on Semantics, Knowledge, and Grid, SKG 2007, 2007, pp. 20 - 25
Issue Date:: 2007-12-01

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Field	Value	Language
dc.contributor.author	Zhang, Y	en_US
dc.contributor.author	Xu, G https://orcid.org/0000-0003-4493-6663	en_US
dc.date.issued	2007-12-01	en_US
dc.identifier.citation	3rd International Conference on Semantics, Knowledge, and Grid, SKG 2007, 2007, pp. 20 - 25	en_US
dc.identifier.isbn	0769530079	en_US
dc.identifier.isbn	9780769530079	en_US
dc.identifier.uri	http://hdl.handle.net/10453/33797
dc.description.abstract	Due to the lack of a uniform schema for web documents and the sheer amount and dynamics of web data, both the effectiveness and the efficiency of information management and retrieval of web data is often unsatisfactory when using conventional data management and searching techniques. To address this issue, we have adopted web mining and web community analysis approaches. Based on the analysis of web document contents, hyperlinks analysis, user access logs and semantic analysis, we have developed various approaches or algorithms to construct and analyze web communities, and to make recommendations. This paper will introduce and discuss various approaches on web community mining and recommendation. © 2007 IEEE.	en_US
dc.relation.ispartof	3rd International Conference on Semantics, Knowledge, and Grid, SKG 2007	en_US
dc.relation.isbasedon	10.1109/SKG.2007.121	en_US
dc.title	On web communities mining and analysis	en_US
dc.type	Conference Proceeding
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - AAI - Advanced Analytics Institute Research Centre
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

Due to the lack of a uniform schema for web documents and the sheer amount and dynamics of web data, both the effectiveness and the efficiency of information management and retrieval of web data is often unsatisfactory when using conventional data management and searching techniques. To address this issue, we have adopted web mining and web community analysis approaches. Based on the analysis of web document contents, hyperlinks analysis, user access logs and semantic analysis, we have developed various approaches or algorithms to construct and analyze web communities, and to make recommendations. This paper will introduce and discuss various approaches on web community mining and recommendation. © 2007 IEEE.

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http://hdl.handle.net/10453/33797