On the use of words and n-grams for Chinese information retrieval
IRAL '00 Proceedings of the fifth international workshop on on Information retrieval with Asian languages
Mining the peanut gallery: opinion extraction and semantic classification of product reviews
WWW '03 Proceedings of the 12th international conference on World Wide Web
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
A sentimental education: sentiment analysis using subjectivity summarization based on minimum cuts
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Determining the sentiment of opinions
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Sentiment retrieval using generative models
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Information Technology and Management
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This paper presents the results of experiments in which we tested different kinds of features for retrieval of Chinese opinionated texts. We assume that the task of retrieval of opinionated texts (OIR) can be regarded as a subtask of general IR, but with some distinct features. The experiments showed that the best results were obtained from the combination of character-based processing, dictionary look up (maximum matching) and a negation check.