@inproceedings{e7c4619221634535a3a2fb3e7ff1505d,
title = "High precision opinion retrieval using sentiment-relevance flows",
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.",
keywords = "Opinion retrieval, Sentiment analysis, Sentiment-relevance flow",
author = "Lee, {Seung Wook} and Lee, {Jung Tae} and Song, {Young In} and Rim, {Hae Chang}",
year = "2010",
doi = "10.1145/1835449.1835631",
language = "English",
isbn = "9781605588964",
series = "SIGIR 2010 Proceedings - 33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval",
pages = "817--818",
booktitle = "SIGIR 2010 Proceedings - 33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval",
note = "33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2010 ; Conference date: 19-07-2010 Through 23-07-2010",
}