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Probabilistic opinion models based on subjective sources

Belbachir, Faiza and Boughanem, Mohand and Missen, Malik Muhammad Saad Probabilistic opinion models based on subjective sources. (2014) In: ACM Symposium on Applied Computing (SAC), 24 March 2014 - 29 March 2014 (Gyeongju, Korea, Republic Of).

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Official URL: http://dx.doi.org/10.1145/2554850.2555091

Abstract

This article describes approaches for searching opinionated documents for a given query from a standard data collection. To detect if a text is opinionated (i.e., contain subjective information) or not, we propose two methods: the first method is based on lexicons of subjective words (i.e., SentiWordNet) supported by the assumption that more a document contains the subjective terms more it has the tendency of being an opinionated document while the second method is based on probabilistic model supporting the idea that given a document having a strong similarity with a reference opinionated text is more likely to be opinionated. In the second method, we take support of language modeling approach to compute this similarity. Experiments are conducted with TREC Blog06 as the test collection and the IMDB data collection as being the reference data collection. The experimental results report effectiveness of both methods.

Item Type:Conference or Workshop Item (Paper)
Additional Information:Thanks to ACM editor. The definitive version is available at http://dl.acm.org/citation.cfm?id=2555091
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - INPT (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UPS (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
Other partners > The Islamia University of Bahawalpur - IUB (PAKISTAN)
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Deposited By: IRIT IRIT
Deposited On:18 Mar 2015 14:50

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