@inproceedings{57e3c6cea2c047409b9a92f3cc83b266,
title = "Research on feature extraction from Chinese text for opinion mining",
abstract = "More and more users and manufacturers concern about product reviews on the web, but it's difficult to quickly find interesting content from massive information. In order to mine sentiment polarity from review sentences, two approaches for product feature extraction and sentence opinion mining are proposed in this paper. Because of the characteristics of Chinese language, lexical analyzing tools are used to process review text, and association rule model is used to mine frequent items as candidate feature. In order to get better result, several filtering algorithms are proposed. Experiment results demonstrate that relation between the precision and recall rate of feature extraction task with different minimum support thresholds in association rules mining, and the promising performance of our approach has also been shown.",
keywords = "Association rule model, Feature extraction, Opinion mining, Sentiment detection",
author = "Shanzong Zhu and Yuanchao Liu and Ming Liu and Peiliang Tian",
year = "2009",
doi = "10.1109/IALP.2009.11",
language = "英语",
isbn = "9780769539041",
series = "2009 International Conference on Asian Language Processing: Recent Advances in Asian Language Processing, IALP 2009",
pages = "7--10",
booktitle = "2009 International Conference on Asian Language Processing",
note = "2009 International Conference on Asian Language Processing: Recent Advances in Asian Language Processing, IALP 2009 ; Conference date: 07-12-2009 Through 09-12-2009",
}