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| HAL : lirmm-00401363, version 1 |
| Fiche détaillée |  Récupérer au format |
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| Intelligent Data Analysis Journal 14 (2010) 20 |
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| Extraction of Unexpected Sentences: A Sentiment Classification Assessed Approach |
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| Haoyuan Li 1, 2Anne Laurent 1 |
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| (2010) |
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| Sentiment classification in text documents is an active data mining research topic in opinion retrieval and analysis. Different from previous studies concentrating on the development of effective classifiers, in this paper, we focus on the extraction and validation of unexpected sentences issued in sentiment classification. In this paper, we propose a general framework for determining unexpected sentences. The relevance of the extracted unexpected sentences is assessed in the context of text classification. In the experiments, we present the extraction of unexpected sentences for sentiment classification within the proposed framework, and then evaluate the influence of unexpected sentences on the quality of classification tasks. The experimental results show the effectiveness and usefulness of our proposed approach. |
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| 1 : | Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM) |
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CNRS : UMR5506 – Université Montpellier II - Sciences et Techniques du Languedoc |
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| 2 : | Laboratoire de Génie Informatique et Ingénierie de Production (LGI2P) |
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Ecole des Mines d'Alès |
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| 3 : | Laboratoire de Recherche en Informatique (LRI) |
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CNRS : UMR8623 – Université Paris XI - Paris Sud |
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| [INFO/TAL : Traitement Algorithmique du Langage][INFO/TATOO] |
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| Domaine | : | Informatique/Recherche d'information |
| lirmm-00401363, version 1 | |
| http://hal-lirmm.ccsd.cnrs.fr/lirmm-00401363 | |
| oai:hal-lirmm.ccsd.cnrs.fr:lirmm-00401363 | |
| Contributeur : Haoyuan Li | |
| Soumis le : Jeudi 2 Juillet 2009, 21:47:34 | |
| Dernière modification le : Mercredi 27 Avril 2011, 10:28:27 | |
