TY - GEN
T1 - Emotional element extraction based on CRFs
AU - Wang, Yashen
AU - Liu, Quanchao
AU - Huang, Heyan
N1 - Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2014.
PY - 2014
Y1 - 2014
N2 - As the fast development of social network and electronic business, a huge number of comments are generated by users every day. Extraction of emotional elements is an important pre-task of sentiment analysis and opinion mining for comments. In this paper, we extract the emotional elements such as the opinion holder, the comment target, and the evaluation phrase, which previous researches rarely concerned about, especially in Chinese. Based on Conditional Random Fields, we label the evaluation phrase which structure is simple. Then on account of unique characteristics of grammar and syntax of Chinese, we design several rule-based methods to extract evaluation phrase which is in complex structure, as well as comment targets and opinion holders. According to the experimental results, our method improves the performance of emotional element extraction in the domain of sentiment analysis for automobile’s Chinese comments. And it also contributes greatly to our subsequent task such as sentiment analysis of social media or comments from other domains.
AB - As the fast development of social network and electronic business, a huge number of comments are generated by users every day. Extraction of emotional elements is an important pre-task of sentiment analysis and opinion mining for comments. In this paper, we extract the emotional elements such as the opinion holder, the comment target, and the evaluation phrase, which previous researches rarely concerned about, especially in Chinese. Based on Conditional Random Fields, we label the evaluation phrase which structure is simple. Then on account of unique characteristics of grammar and syntax of Chinese, we design several rule-based methods to extract evaluation phrase which is in complex structure, as well as comment targets and opinion holders. According to the experimental results, our method improves the performance of emotional element extraction in the domain of sentiment analysis for automobile’s Chinese comments. And it also contributes greatly to our subsequent task such as sentiment analysis of social media or comments from other domains.
KW - Comment target
KW - Evaluation phrase
KW - Information extraction
KW - Opinion analysis
KW - Opinion holder
UR - http://www.scopus.com/inward/record.url?scp=84921846352&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-54927-4_48
DO - 10.1007/978-3-642-54927-4_48
M3 - Conference contribution
AN - SCOPUS:84921846352
T3 - Advances in Intelligent Systems and Computing
SP - 507
EP - 517
BT - Practical Applications of Intelligent Systems - Proceedings of the 8th International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2013
A2 - Wen, Zhenkun
A2 - Li, Tianrui
PB - Springer Verlag
T2 - 8th International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2013
Y2 - 20 November 2013 through 23 November 2013
ER -