Abstract
With the development of social media, massive reviews are generated by users every day. The extraction of evaluative information, including opinion holder, comment target and evaluation phrase, is an important pre-task of opinion analysis and also in great need, especially for Chinese text. This paper proposes an efficient method for extracting Chinese evaluation phrase based on cascaded model and mainly makes three contributions: (i) to implement and evaluate the method, we construct an original annotated corpus for Chinese evaluation phrase of automobile; (ii) based on Conditional Random Fields, we identify the evaluation phrase which is in simple structure; (iii) three kinds of rule-based methods, such as parenthesis/preposition/adverb phrase rule, are designed to extract evaluation phrase in complex structure. According to the experiment results, the proposed method performs well. Meanwhile it contributes greatly to our subsequent tasks, such as sentiment analysis of social media.
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Wang, Y., Feng, C., Liu, Q., Huang, H. (2014). Chinese Evaluation Phrase Extraction Based on Cascaded Model. In: Li, F., Li, G., Hwang, Sw., Yao, B., Zhang, Z. (eds) Web-Age Information Management. WAIM 2014. Lecture Notes in Computer Science, vol 8485. Springer, Cham. https://doi.org/10.1007/978-3-319-08010-9_21
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DOI: https://doi.org/10.1007/978-3-319-08010-9_21
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08009-3
Online ISBN: 978-3-319-08010-9
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