TY - GEN
T1 - Learning multilinguistic knowledge for opinion analysis
AU - Xu, Ruifeng
AU - Wong, Kam Fai
AU - Lu, Qin
AU - Xia, Yunqing
PY - 2008/11/27
Y1 - 2008/11/27
N2 - Most existing opinion analysis techniques used word-level sentiment knowledge but lack the learning capacity on the behaviors of context-dependent opinion words. Meanwhile, the use of collocation-level sentiment knowledge is not well studied. This paper presents an opinion analysis system, namely OA, which incorporates the word-level and collocation-level sentiment knowledge. Based on the observation on the NTCIR-6 opinion training corpus, some word-level and collocation-level linguistic clues for opinion analysis are discovered. Learning techniques are developed to learn the features corresponding to these discovered clues. These features are in turn incorporated into a classifier based on support vector machine to identify opinionated sentences and determine their polarities from running text. Evaluations on NTCIR-6 opinion testing dataset show that OA achieved promising overall performance.
AB - Most existing opinion analysis techniques used word-level sentiment knowledge but lack the learning capacity on the behaviors of context-dependent opinion words. Meanwhile, the use of collocation-level sentiment knowledge is not well studied. This paper presents an opinion analysis system, namely OA, which incorporates the word-level and collocation-level sentiment knowledge. Based on the observation on the NTCIR-6 opinion training corpus, some word-level and collocation-level linguistic clues for opinion analysis are discovered. Learning techniques are developed to learn the features corresponding to these discovered clues. These features are in turn incorporated into a classifier based on support vector machine to identify opinionated sentences and determine their polarities from running text. Evaluations on NTCIR-6 opinion testing dataset show that OA achieved promising overall performance.
KW - Collocation
KW - Linguistic Knowledge Learning
KW - Opinion Analysis
UR - http://www.scopus.com/inward/record.url?scp=56549107170&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-87442-3_122
DO - 10.1007/978-3-540-87442-3_122
M3 - Conference article published in proceeding or book
SN - 3540874402
SN - 9783540874409
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 993
EP - 1000
BT - Advanced Intelligent Computing Theories and Applications
T2 - 4th International Conference on Intelligent Computing, ICIC 2008
Y2 - 15 September 2008 through 18 September 2008
ER -