Paper: Opinion Extraction Using a Learning-Based Anaphora Resolution Technique

ACL ID I05-2030
Title Opinion Extraction Using a Learning-Based Anaphora Resolution Technique
Venue International Joint Conference on Natural Language Processing
Session poster-demo-tutorial
Year 2005
Authors

This paper addresses the task of extract- ing opinions from a given document collection. Assuming that an opinion can be represented as a tuple 〈Subject, Attribute, Value〉, we propose a compu- tational method to extract such tuples from texts. In this method, the main task is decomposed into (a) the pro- cess of extracting Attribute-Value pairs from a given text and (b) the process of judging whether an extracted pair ex- presses an opinion of the author. We apply machine-learning techniques to both subtasks. We also report on the results of our experiments and discuss future directions.