TY - GEN
T1 - Chinese evaluation phrase extraction based on cascaded model
AU - Wang, Yashen
AU - Feng, Chong
AU - Liu, Quanchao
AU - Huang, Heyan
PY - 2014
Y1 - 2014
N2 - 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.
AB - 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.
KW - Data Mining
KW - Evaluation Phrase
KW - Information Extraction
UR - http://www.scopus.com/inward/record.url?scp=84958554223&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-08010-9_21
DO - 10.1007/978-3-319-08010-9_21
M3 - Conference contribution
AN - SCOPUS:84958554223
SN - 9783319080093
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 192
EP - 203
BT - Web-Age Information Management - 15th International Conference, WAIM 2014, Proceedings
PB - Springer Verlag
T2 - 15th International Conference on Web-Age Information Management, WAIM 2014
Y2 - 16 June 2014 through 18 June 2014
ER -