PKUTM Experiments in NTCIR-8 MOAT Task
نویسندگان
چکیده
This paper describes our work in the Simplified Chinese opinion analysis tasks in NTCIR-8. In the task of detecting opinioned sentences, various sentiment lexicons are used, including opinion indicators, opinion operators, degree adverbs and opinion words. The linear SVM model is selected as the main classifier, and four groups of features are extracted according to punctuations, words and sentiment lexicons. We also try a two-step classification to improve the SVM result. For extracting the opinion holder and target, we use a synthesis of CRF and heuristic rules. The evaluation results on NTCIR-8 MOAT Simplified Chinese side show that our system achieves the best fmeasure in two tasks. This demonstrates that the proposed framework is promising.
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