TY - GEN
T1 - Corse-fine opinion mining
AU - Xu, Ruifeng
AU - Kit, Chunyu
PY - 2009
Y1 - 2009
N2 - Most existing opinion mining systems recognize opinionated sentences and determine their polarity as one-step classification procedure. This paper proposes a different multi-pass coarse-fine opinion mining framework. In this framework, a base classifier firstly coarsely estimates the opinion of sentences. The obtained sentence-, paragraph- and document-level opinions are incorporated in an improved classifier as features to re-estimate the opinion of sentences. The updated opinions are feed back to the classifier for further refining the sentence opinion until the classifier outputs converge. Three base classifiers are incorporated in this coarse-fine opinion mining framework, respectively. Their performances are evaluated on NTCIR-6 and NTCIR-7 opinion analysis dataset. The achieved performance improvements show that the proposed coarse-fine strategy is effective to improve the developed opinion mining classifiers. © 2009 IEEE.
AB - Most existing opinion mining systems recognize opinionated sentences and determine their polarity as one-step classification procedure. This paper proposes a different multi-pass coarse-fine opinion mining framework. In this framework, a base classifier firstly coarsely estimates the opinion of sentences. The obtained sentence-, paragraph- and document-level opinions are incorporated in an improved classifier as features to re-estimate the opinion of sentences. The updated opinions are feed back to the classifier for further refining the sentence opinion until the classifier outputs converge. Three base classifiers are incorporated in this coarse-fine opinion mining framework, respectively. Their performances are evaluated on NTCIR-6 and NTCIR-7 opinion analysis dataset. The achieved performance improvements show that the proposed coarse-fine strategy is effective to improve the developed opinion mining classifiers. © 2009 IEEE.
KW - Classifier
KW - Coarse-fine opinion mining
KW - Opinion analysis
KW - Opinion mining
UR - https://www.scopus.com/pages/publications/70350736120
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-70350736120&origin=recordpage
U2 - 10.1109/ICMLC.2009.5212768
DO - 10.1109/ICMLC.2009.5212768
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781424437030
VL - 6
SP - 3469
EP - 3474
BT - Proceedings of the 2009 International Conference on Machine Learning and Cybernetics
T2 - 2009 International Conference on Machine Learning and Cybernetics
Y2 - 12 July 2009 through 15 July 2009
ER -