{"id":148278,"date":"2006-01-01T00:00:00","date_gmt":"2006-01-01T00:00:00","guid":{"rendered":"https:\/\/newed.any0.dpdns.org\/en-us\/research\/msr-research-item\/opinion-mining-on-the-web-by-extracting-subject-aspect-evaluation-relasions\/"},"modified":"2018-10-16T20:56:13","modified_gmt":"2018-10-17T03:56:13","slug":"opinion-mining-on-the-web-by-extracting-subject-aspect-evaluation-relasions","status":"publish","type":"msr-research-item","link":"https:\/\/newed.any0.dpdns.org\/en-us\/research\/publication\/opinion-mining-on-the-web-by-extracting-subject-aspect-evaluation-relasions\/","title":{"rendered":"Opinion Mining on the Web by Extracting Subject-Aspect-Evaluation Relasions"},"content":{"rendered":"<div class=\"asset-content\">\n<p>This paper addresses the task of extracting opinions from a given document collection. Assuming that an opinion can be represented as a tuple &#8220;Subject, Aspect, Evaluation,&#8221; we propose a computational method to extract such tuples from texts. In this method, the main task is decomposed into (a) the process of extracting Aspect-Evaluation pairs from a given text and (b) the process of judging whether an extracted pair expresses 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.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>This paper addresses the task of extracting opinions from a given document collection. Assuming that an opinion can be represented as a tuple &#8220;Subject, Aspect, Evaluation,&#8221; we propose a computational method to extract such tuples from texts. 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