Qiang Huang


2020

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A Joint Model for Aspect-Category Sentiment Analysis with Shared Sentiment Prediction Layer
Yuncong Li | Zhe Yang | Cunxiang Yin | Xu Pan | Lunan Cui | Qiang Huang | Ting Wei
Proceedings of the 19th Chinese National Conference on Computational Linguistics

Aspect-category sentiment analysis (ACSA) aims to predict the aspect categories mentioned in texts and their corresponding sentiment polarities. Some joint models have been proposed to address this task. Given a text, these joint models detect all the aspect categories mentioned in the text and predict the sentiment polarities toward them at once. Although these joint models obtain promising performances, they train separate parameters for each aspect category and therefore suffer from data deficiency of some aspect categories. To solve this problem, we propose a novel joint model which contains a shared sentiment prediction layer. The shared sentiment prediction layer transfers sentiment knowledge between aspect categories and alleviates the problem caused by data deficiency. Experiments conducted on SemEval-2016 Datasets demonstrate the effectiveness of our model.

2015

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Chinese Spelling Check System Based on N-gram Model
Weijian Xie | Peijie Huang | Xinrui Zhang | Kaiduo Hong | Qiang Huang | Bingzhou Chen | Lei Huang
Proceedings of the Eighth SIGHAN Workshop on Chinese Language Processing

2014

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Ch2R: A Chinese Chatter Robot for Online Shopping Guide
Peijie Huang | Xianmao Lin | Zeqi Lian | De Yang | Xiaoling Tang | Li Huang | Qiang Huang | Xiupeng Wu | Guisheng Wu | Xinrui Zhang
Proceedings of the Third CIPS-SIGHAN Joint Conference on Chinese Language Processing

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Chinese Spelling Check System Based on Tri-gram Model
Qiang Huang | Peijie Huang | Xinrui Zhang | Weijian Xie | Kaiduo Hong | Bingzhou Chen | Lei Huang
Proceedings of the Third CIPS-SIGHAN Joint Conference on Chinese Language Processing

2004

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Automatic Call Routing with Multiple Language Models
Qiang Huang | Stephen Cox
Proceedings of the HLT-NAACL 2004 Workshop on Spoken Language Understanding for Conversational Systems and Higher Level Linguistic Information for Speech Processing