Lishuang Li


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Hierarchical Attention Based Position-Aware Network for Aspect-Level Sentiment Analysis
Lishuang Li | Yang Liu | AnQiao Zhou
Proceedings of the 22nd Conference on Computational Natural Language Learning

Aspect-level sentiment analysis aims to identify the sentiment of a specific target in its context. Previous works have proved that the interactions between aspects and the contexts are important. On this basis, we also propose a succinct hierarchical attention based mechanism to fuse the information of targets and the contextual words. In addition, most existing methods ignore the position information of the aspect when encoding the sentence. In this paper, we argue that the position-aware representations are beneficial to this task. Therefore, we propose a hierarchical attention based position-aware network (HAPN), which introduces position embeddings to learn the position-aware representations of sentences and further generate the target-specific representations of contextual words. The experimental results on SemEval 2014 dataset show that our approach outperforms the state-of-the-art methods.


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Extracting Biomedical Event Using Feature Selection and Word Representation
Xinyu He | Lishuang Li | Jieqiong Zheng | Meiyue Qin
Proceedings of the 4th BioNLP Shared Task Workshop


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Improving Feature-Based Biomedical Event Extraction System by Integrating Argument Information
Lishuang Li | Yiwen Wang | Degen Huang
Proceedings of the BioNLP Shared Task 2013 Workshop


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Mining Large-scale Comparable Corpora from Chinese-English News Collections
Degen Huang | Lian Zhao | Lishuang Li | Haitao Yu
Coling 2010: Posters


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HMM and CRF Based Hybrid Model for Chinese Lexical Analysis
Degen Huang | Xiao Sun | Shidou Jiao | Lishuang Li | Zhuoye Ding | Ru Wan
Proceedings of the Sixth SIGHAN Workshop on Chinese Language Processing


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Hybrid Models for Chinese Named Entity Recognition
Lishuang Li | Tingting Mao | Degen Huang | Yuansheng Yang
Proceedings of the Fifth SIGHAN Workshop on Chinese Language Processing