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Transverse Subjectivity Classification| old_uid | 11427 |
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| title | Transverse Subjectivity Classification |
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| start_date | 2012/05/24 |
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| schedule | 10h30 |
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| online | no |
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| location_info | salle 25-26/105 |
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| summary | In this talk, we will present our research on learning models for subjectivity classification across domain. After a small introduction about related works and challenges of sentiment analysis, we will start by presenting new features for subjectivity analysis.
Then, we will present two different paradigms of multi-view learning strategies to learn transfer models: multi-view learning with agreement and guided multi-view learning. Then, we will present an exhaustive evaluation based on both paradigms including two states-of-the-art algorithms and show that accuracy over 91% can be obtained using three views. In our concluding remarks, we will talk about future extensions of the presented methodology. |
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| responsibles | Revault d'Allonnes |
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