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Conference Paper: Automatic online monitoring and data-mining internet forums

TitleAutomatic online monitoring and data-mining internet forums
Authors
KeywordsDatamining
Internet Forum
Internet Surveillance
Web Crawler
Issue Date2011
Citation
Proceedings - 7Th International Conference On Intelligent Information Hiding And Multimedia Signal Processing, Iihmsp 2011, 2011, p. 384-387 How to Cite?
AbstractWith the advancement of internet technology and the change in the mode of communication, it is found that much first-hand news have been discussed in Internet forums well before they are reported in traditional mass media. Also, this communication channel provides an effective channel for illegal activities such as dissemination of copyrighted movies, threatening messages and online gambling etc. The law enforcement agencies are looking for solutions to monitor these discussion forums for possible criminal activities and download suspected postings as evidence for investigation. The volume of postings is huge, for 10 popular forums in Hong Kong, we found that there are 300,000 new messages every day. In this paper, we propose an automatic system that tackles this problem. Our proposed system will download postings from selected discussion forums continuously and employ data mining techniques to identify hot topics and cluster authors into different groups using word-based user profiles. Difference techniques are applied to process the collected data and several ways are proposed to solve the problem. © 2011 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/152023
References

 

DC FieldValueLanguage
dc.contributor.authorLai, YMen_US
dc.contributor.authorZheng, Xen_US
dc.contributor.authorChow, KPen_US
dc.contributor.authorHui, LCKen_US
dc.contributor.authorYiu, SMen_US
dc.date.accessioned2012-06-26T06:32:36Z-
dc.date.available2012-06-26T06:32:36Z-
dc.date.issued2011en_US
dc.identifier.citationProceedings - 7Th International Conference On Intelligent Information Hiding And Multimedia Signal Processing, Iihmsp 2011, 2011, p. 384-387en_US
dc.identifier.urihttp://hdl.handle.net/10722/152023-
dc.description.abstractWith the advancement of internet technology and the change in the mode of communication, it is found that much first-hand news have been discussed in Internet forums well before they are reported in traditional mass media. Also, this communication channel provides an effective channel for illegal activities such as dissemination of copyrighted movies, threatening messages and online gambling etc. The law enforcement agencies are looking for solutions to monitor these discussion forums for possible criminal activities and download suspected postings as evidence for investigation. The volume of postings is huge, for 10 popular forums in Hong Kong, we found that there are 300,000 new messages every day. In this paper, we propose an automatic system that tackles this problem. Our proposed system will download postings from selected discussion forums continuously and employ data mining techniques to identify hot topics and cluster authors into different groups using word-based user profiles. Difference techniques are applied to process the collected data and several ways are proposed to solve the problem. © 2011 IEEE.en_US
dc.languageengen_US
dc.relation.ispartofProceedings - 7th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP 2011en_US
dc.subjectDataminingen_US
dc.subjectInternet Forumen_US
dc.subjectInternet Surveillanceen_US
dc.subjectWeb Crawleren_US
dc.titleAutomatic online monitoring and data-mining internet forumsen_US
dc.typeConference_Paperen_US
dc.identifier.emailChow, KP:chow@cs.hku.hken_US
dc.identifier.emailHui, LCK:hui@cs.hku.hken_US
dc.identifier.emailYiu, SM:smyiu@cs.hku.hken_US
dc.identifier.authorityChow, KP=rp00111en_US
dc.identifier.authorityHui, LCK=rp00120en_US
dc.identifier.authorityYiu, SM=rp00207en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1109/IIHMSP.2011.71en_US
dc.identifier.scopuseid_2-s2.0-83455212247en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-83455212247&selection=ref&src=s&origin=recordpageen_US
dc.identifier.spage384en_US
dc.identifier.epage387en_US
dc.identifier.scopusauthoridLai, YM=7401512091en_US
dc.identifier.scopusauthoridZheng, X=54685651900en_US
dc.identifier.scopusauthoridChow, KP=7202180751en_US
dc.identifier.scopusauthoridHui, LCK=8905728300en_US
dc.identifier.scopusauthoridYiu, SM=7003282240en_US

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