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Lsislif: CRF and Logistic Regression for Opinion Target Extraction and Sentiment Polarity Analysis
Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015)
This paper describes our contribution in Opinion Target Extraction OTE and Sentiment Polarity sub tasks of SemEval 2015 ABSA task. A CRF model with IOB notation has been adopted for OTE with several groups of features including syntactic, lexical, semantic, sentiment lexicon features. Our submission for OTE is ranked fifth over twenty submissions. A Logistic Regression model with a weighting schema of positive and negative labels have been used for sentiment polarity; several groups of featuresdoi:10.18653/v1/s15-2128 dblp:conf/semeval/HamdanBB15a fatcat:r2cqkp2zinezxichqr3pho5lbu