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dc.contributor.authorSarencheh, S.
dc.contributor.authorPotdar, Vidyasagar
dc.contributor.authorYeganeh, E.
dc.contributor.authorFiroozeh, N.
dc.contributor.editorDavid Taniar, Osvaldo Gervasi, Beniamino Murgante, Eric Pardede and Bernady O Apduhan
dc.identifier.citationSarencheh, Saeed and Potdar, Vidyasagar and Yeganeh, Elham and Firoozeh, Nazanin. 2010. Semi-Automatic Information Extraction from Discussion Boards with Applications for Anti-Spam Technology, in Taniar, D. and Gervasi, O. and Murgante, B. and Pardede, E. and Apduhan, B.O. (ed), Lecture Notes in Computer Science, Volume 6017: Computational science and its applications - ICCSA 2010, pp. 370-382. Germany: Springer.

Forums (or discussion boards) represent a huge information collection structured under different boards, threads and posts. The actual information entity of a forum is a post, which has the information about authors, date and time of post, actual content etc. This information is significant for a number of applications like gathering market intelligence, analyzing customer perceptions etc. However automatically extracting this information from a forum is an extremely challenging task. There are several customized parsers designed for extracting information from a particular forum platform with a specific template (e.g. SMF or phpBB), however the problem with this approach is that these parsers are dependent upon the forum platform and the template used, which makes it unrealistic to use in practical situations. Hence, in this paper we propose a semi-automatic rule based solution for extracting forum post information and inserting the extracted information to a database for the purpose of analysis. The key challenge with this solution is identifying extraction rules, which are normally forum platform and forum template specific. As a result we analyzed 100 forums to derive these rules and test the performance of the algorithm. The results indicate that we were able to extract all the required information from SMF and phpBB forum platforms, which represent the majority of forums on the web.

dc.subjectInformation extraction
dc.titleSemi-Automatic Information Extraction from Discussion Boards with Applications for Anti-Spam Technology
dc.typeBook Chapter
dcterms.source.titleLecture notes in computer science, volume 6017: computational science and its applications - ICCSA 2010
curtin.departmentCentre for Extended Enterprises and Business Intelligence
curtin.accessStatusFulltext not available

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