Identifying sources of opinions with conditional random fields and extraction patterns

摘要: Recent systems have been developed for sentiment classification, opinion recognition, and analysis (e.g., detecting polarity strength). We pursue another aspect of analysis: identifying the sources opinions, emotions, sentiments. view this problem as an information extraction task adopt a hybrid approach that combines Conditional Random Fields (Lafferty et al., 2001) variation AutoSlog (Riloff, 1996a). While CRFs model source identification sequence tagging task, learns patterns. Our results show combination these two methods performs better than either one alone. The resulting system identifies with 79.3% precision 59.5% recall using head noun matching measure, 81.2% 60.6% overlap measure.