Transverse Subjectivity Classification

old_uid11427
titleTransverse Subjectivity Classification
start_date2012/05/24
schedule10h30
onlineno
location_infosalle 25-26/105
summaryIn 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.
responsiblesRevault d'Allonnes