High precision opinion retrieval using sentiment-relevance flows

Authors:
Seung-Wook Lee;Jung-Tae Lee;Young-In Song;Hae-Chang Rim
Affiliations:
Korea University, Seoul, South Korea;Korea University, Seoul, South Korea;Microsoft Research Asia, Beijing, China;Korea University, Seoul, South Korea
Venue:
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Year:
2010

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Abstract

Opinion retrieval involves the measuring of opinion score of a document about the given topic. We propose a new method, namely sentiment-relevance flow, that naturally unifies the topic relevance and the opinionated nature of a document. Experiments conducted over a large-scaled Web corpus show that the proposed approach improves performance of opinion retrieval in terms of precision at top ranks.