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Identifying sources of opinions with conditional random fields and extraction patterns
2005
Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing - HLT '05
unpublished
Recent systems have been developed for sentiment classification, opinion recognition, and opinion analysis (e.g., detecting polarity and strength). We pursue another aspect of opinion analysis: identifying the sources of opinions, emotions, and sentiments. We view this problem as an information extraction task and adopt a hybrid approach that combines Conditional Random Fields (Lafferty et al., 2001 ) and a variation of AutoSlog (Riloff, 1996a). While CRFs model source identification as a
doi:10.3115/1220575.1220620
fatcat:gh32j6j2bzgwxi4vbqpg2vjb6i