Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
Effects of adjective orientation and gradability on sentence subjectivity
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Thumbs up?: sentiment classification using machine learning techniques
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
Morpheme-based derivation of bipolar semantic orientation of Chinese words
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Determining the sentiment of opinions
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
A holistic lexicon-based approach to opinion mining
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Chinese word segmentation as morpheme-based lexical chunking
Information Sciences: an International Journal
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
Recognizing contextual polarity: An exploration of features for phrase-level sentiment analysis
Computational Linguistics
Using morphological and syntactic structures for Chinese opinion analysis
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 3
Learning lexical subjectivity strength for chinese opinionated sentence identification
CICLing'12 Proceedings of the 13th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I
A weakly supervised model for sentence-level semantic orientation analysis with multiple experts
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Set-Similarity joins based semi-supervised sentiment analysis
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part I
| Hi-index | 0.00 |
This paper presents a fuzzy set theory based approach to Chinese sentence-level sentiment classification. Compared with traditional topic-based text classification techniques, the fuzzy set theory provides a straightforward way to model the intrinsic fuzziness between sentiment polarity classes. To approach fuzzy sentiment classification, we first propose a fine-to-coarse strategy to estimate sentence sentiment intensity. Then, we define three fuzzy sets to represent the respective sentiment polarity classes, namely positive, negative and neutral sentiments. Based on sentence sentiment intensities, we further build membership functions to indicate the degrees of an opinionated sentence in different fuzzy sets. Finally, we determine sentence-level polarity under maximum membership principle. We show that our approach can achieve promising performance on the test set for Chinese opinion analysis pilot task at NTCIR-6.