@inproceedings{a0cad2bb3f8048e19707cf79c7e08315,
title = "ECNU: Extracting Effective Features from Multiple Sequential Sentences for Target-dependent Sentiment Analysis in Reviews",
abstract = "This paper describes our systems submitted to the target-dependent sentiment polarity classification subtask in aspect based sentiment analysis (ABSA) task (i.e., Task 12) in SemEval 2015. To settle this problem, we extracted several effective features from three sequential sentences, including sentiment lexicon, linguistic and domain specific features. Then we employed these features to construct classifiers using supervised classification algorithm. In laptop domain, our systems ranked 2nd out of 6 constrained submissions and 2nd out of 7 unconstrained submissions. In restaurant domain, the rankings are 5th out of 6 and 2nd out of 8 respectively.",
author = "Zhihua Zhang and Man Lan",
note = "Publisher Copyright: {\textcopyright} 2015 Association for Computational Linguistics; 9th International Workshop on Semantic Evaluation, SemEval 2015 co-located with the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2015 ; Conference date: 04-06-2015 Through 05-06-2015",
year = "2015",
doi = "10.18653/v1/s15-2125",
language = "英语",
series = "SemEval 2015 - 9th International Workshop on Semantic Evaluation, co-located with the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2015 - Proceedings",
publisher = "Association for Computational Linguistics (ACL)",
pages = "736--741",
editor = "Preslav Nakov and Torsten Zesch and Daniel Cer and David Jurgens",
booktitle = "SemEval 2015 - 9th International Workshop on Semantic Evaluation, co-located with the 2015 Conference of the North American Chapter of the Association for Computational Linguistics",
address = "澳大利亚",
}