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2009 International Conference on Advanced Information Networking and Applications Workshops
Sentence-Level Opinion-Topic Association for Opinion Detection in Blogs
Bradford, United Kingdom
May 26-May 29
ISBN: 978-0-7695-3639-2
| ASCII Text | x | ||
| Malik Muhammad Saad Missen, Mohand Boughanem, "Sentence-Level Opinion-Topic Association for Opinion Detection in Blogs," Advanced Information Networking and Applications Workshops, International Conference on, pp. 733-737, 2009 International Conference on Advanced Information Networking and Applications Workshops, 2009. | |||
| BibTex | x | ||
| @article{ 10.1109/WAINA.2009.157, author = {Malik Muhammad Saad Missen and Mohand Boughanem}, title = {Sentence-Level Opinion-Topic Association for Opinion Detection in Blogs}, journal ={Advanced Information Networking and Applications Workshops, International Conference on}, volume = {0}, year = {2009}, isbn = {978-0-7695-3639-2}, pages = {733-737}, doi = {http://doi.ieeecomputersociety.org/10.1109/WAINA.2009.157}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - Advanced Information Networking and Applications Workshops, International Conference on TI - Sentence-Level Opinion-Topic Association for Opinion Detection in Blogs SN - 978-0-7695-3639-2 SP733 EP737 A1 - Malik Muhammad Saad Missen, A1 - Mohand Boughanem, PY - 2009 KW - Opinion Detection KW - wordNet KW - Information Retrieval VL - 0 JA - Advanced Information Networking and Applications Workshops, International Conference on ER - | |||
The Opinion Detection from blogs has always been a challenge for researchers. One of the challenges faced is to find such documents that specifically contain opinion on users' information need. This requires text processing on sentence level rather than on document level. In this paper, we have proposed an opinion detection approach. The proposed approach tries to tackle opinion detection problem by using some document level heuristics and processing documents on sentence level using different semantic similarity relations of WordNet between sentence words and list of weighted query terms expanded through encyclopedia Wikipedia. According to initial results, our approach performs well with MAP of 0.2177 with improvement of 28.89% over baseline results obtained through BM25 matching formula. TREC Blog 2006 data is used as test data collection.
Index Terms:
Opinion Detection, wordNet, Information Retrieval
Citation:
Malik Muhammad Saad Missen, Mohand Boughanem, "Sentence-Level Opinion-Topic Association for Opinion Detection in Blogs," waina, pp.733-737, 2009 International Conference on Advanced Information Networking and Applications Workshops, 2009
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