Semi-Automatic Information Extraction from Discussion Boards with Applications for Anti-Spam Technology
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 nu...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Book Chapter |
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Springer
2010
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| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11937/11240 |
| _version_ | 1848747752440201216 |
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| author | Sarencheh, S. Potdar, Vidyasagar Yeganeh, E. Firoozeh, N. |
| author2 | David Taniar |
| author_facet | David Taniar Sarencheh, S. Potdar, Vidyasagar Yeganeh, E. Firoozeh, N. |
| author_sort | Sarencheh, S. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T06:54:08Z |
| format | Book Chapter |
| id | curtin-20.500.11937-11240 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T06:54:08Z |
| publishDate | 2010 |
| publisher | Springer |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-112402022-12-09T07:12:37Z Semi-Automatic Information Extraction from Discussion Boards with Applications for Anti-Spam Technology Sarencheh, S. Potdar, Vidyasagar Yeganeh, E. Firoozeh, N. David Taniar Osvaldo Gervasi Beniamino Murgante Eric Pardede Bernady O Apduhan Information extraction Forum 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. 2010 Book Chapter http://hdl.handle.net/20.500.11937/11240 Springer restricted |
| spellingShingle | Information extraction Forum Sarencheh, S. Potdar, Vidyasagar Yeganeh, E. Firoozeh, N. Semi-Automatic Information Extraction from Discussion Boards with Applications for Anti-Spam Technology |
| title | Semi-Automatic Information Extraction from Discussion Boards with Applications for Anti-Spam Technology |
| title_full | Semi-Automatic Information Extraction from Discussion Boards with Applications for Anti-Spam Technology |
| title_fullStr | Semi-Automatic Information Extraction from Discussion Boards with Applications for Anti-Spam Technology |
| title_full_unstemmed | Semi-Automatic Information Extraction from Discussion Boards with Applications for Anti-Spam Technology |
| title_short | Semi-Automatic Information Extraction from Discussion Boards with Applications for Anti-Spam Technology |
| title_sort | semi-automatic information extraction from discussion boards with applications for anti-spam technology |
| topic | Information extraction Forum |
| url | http://hdl.handle.net/20.500.11937/11240 |