Liang-Chih Yu

Also published as: Liang-chih Yu


2019

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Investigating Dynamic Routing in Tree-Structured LSTM for Sentiment Analysis
Jin Wang | Liang-Chih Yu | K. Robert Lai | Xuejie Zhang
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)

Deep neural network models such as long short-term memory (LSTM) and tree-LSTM have been proven to be effective for sentiment analysis. However, sequential LSTM is a bias model wherein the words in the tail of a sentence are more heavily emphasized than those in the header for building sentence representations. Even tree-LSTM, with useful structural information, could not avoid the bias problem because the root node will be dominant and the nodes in the bottom of the parse tree will be less emphasized even though they may contain salient information. To overcome the bias problem, this study proposes a capsule tree-LSTM model, introducing a dynamic routing algorithm as an aggregation layer to build sentence representation by assigning different weights to nodes according to their contributions to prediction. Experiments on Stanford Sentiment Treebank (SST) for sentiment classification and EmoBank for regression show that the proposed method improved the performance of tree-LSTM and other neural network models. In addition, the deeper the tree structure, the bigger the improvement.

2017

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IJCNLP-2017 Task 2: Dimensional Sentiment Analysis for Chinese Phrases
Liang-Chih Yu | Lung-Hao Lee | Jin Wang | Kam-Fai Wong
Proceedings of the IJCNLP 2017, Shared Tasks

This paper presents the IJCNLP 2017 shared task on Dimensional Sentiment Analysis for Chinese Phrases (DSAP) which seeks to identify a real-value sentiment score of Chinese single words and multi-word phrases in the both valence and arousal dimensions. Valence represents the degree of pleasant and unpleasant (or positive and negative) feelings, and arousal represents the degree of excitement and calm. Of the 19 teams registered for this shared task for two-dimensional sentiment analysis, 13 submitted results. We expected that this evaluation campaign could produce more advanced dimensional sentiment analysis techniques, especially for Chinese affective computing. All data sets with gold standards and scoring script are made publicly available to researchers.

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SentiNLP at IJCNLP-2017 Task 4: Customer Feedback Analysis Using a Bi-LSTM-CNN Model
Shuying Lin | Huosheng Xie | Liang-Chih Yu | K. Robert Lai
Proceedings of the IJCNLP 2017, Shared Tasks

The analysis of customer feedback is useful to provide good customer service. There are a lot of online customer feedback are produced. Manual classification is impractical because the high volume of data. Therefore, the automatic classification of the customer feedback is of importance for the analysis system to identify meanings or intentions that the customer express. The aim of shared Task 4 of IJCNLP 2017 is to classify the customer feedback into six tags categorization. In this paper, we present a system that uses word embeddings to express the feature of the sentence in the corpus and the neural network as the classifier to complete the shared task. And then the ensemble method is used to get final predictive result. The proposed method get ranked first among twelve teams in terms of micro-averaged F1 and second for accura-cy metric.

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應用詞向量於語言樣式探勘之研究 (Mining Language Patterns Using Word Embeddings) [In Chinese]
Xiang Xiao | Shao-Zhen Ye | Liang-Chih Yu | K. Robert Lai
Proceedings of the 29th Conference on Computational Linguistics and Speech Processing (ROCLING 2017)

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YZU-NLP at EmoInt-2017: Determining Emotion Intensity Using a Bi-directional LSTM-CNN Model
Yuanye He | Liang-Chih Yu | K. Robert Lai | Weiyi Liu
Proceedings of the 8th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis

The EmoInt-2017 task aims to determine a continuous numerical value representing the intensity to which an emotion is expressed in a tweet. Compared to classification tasks that identify 1 among n emotions for a tweet, the present task can provide more fine-grained (real-valued) sentiment analysis. This paper presents a system that uses a bi-directional LSTM-CNN model to complete the competition task. Combining bi-directional LSTM and CNN, the prediction process considers both global information in a tweet and local important information. The proposed method ranked sixth among twenty-one teams in terms of Pearson Correlation Coefficient.

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Proceedings of the 4th Workshop on Natural Language Processing Techniques for Educational Applications (NLPTEA 2017)
Yuen-Hsien Tseng | Hsin-Hsi Chen | Lung-Hao Lee | Liang-Chih Yu
Proceedings of the 4th Workshop on Natural Language Processing Techniques for Educational Applications (NLPTEA 2017)

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Refining Word Embeddings for Sentiment Analysis
Liang-Chih Yu | Jin Wang | K. Robert Lai | Xuejie Zhang
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing

Word embeddings that can capture semantic and syntactic information from contexts have been extensively used for various natural language processing tasks. However, existing methods for learning context-based word embeddings typically fail to capture sufficient sentiment information. This may result in words with similar vector representations having an opposite sentiment polarity (e.g., good and bad), thus degrading sentiment analysis performance. Therefore, this study proposes a word vector refinement model that can be applied to any pre-trained word vectors (e.g., Word2vec and GloVe). The refinement model is based on adjusting the vector representations of words such that they can be closer to both semantically and sentimentally similar words and further away from sentimentally dissimilar words. Experimental results show that the proposed method can improve conventional word embeddings and outperform previously proposed sentiment embeddings for both binary and fine-grained classification on Stanford Sentiment Treebank (SST).

2016

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Building Chinese Affective Resources in Valence-Arousal Dimensions
Liang-Chih Yu | Lung-Hao Lee | Shuai Hao | Jin Wang | Yunchao He | Jun Hu | K. Robert Lai | Xuejie Zhang
Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

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Dimensional Sentiment Analysis Using a Regional CNN-LSTM Model
Jin Wang | Liang-Chih Yu | K. Robert Lai | Xuejie Zhang
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

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The NTNU-YZU System in the AESW Shared Task: Automated Evaluation of Scientific Writing Using a Convolutional Neural Network
Lung-Hao Lee | Bo-Lin Lin | Liang-Chih Yu | Yuen-Hsien Tseng
Proceedings of the 11th Workshop on Innovative Use of NLP for Building Educational Applications

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Overview of NLP-TEA 2016 Shared Task for Chinese Grammatical Error Diagnosis
Lung-Hao Lee | Gaoqi Rao | Liang-Chih Yu | Endong Xun | Baolin Zhang | Li-Ping Chang
Proceedings of the 3rd Workshop on Natural Language Processing Techniques for Educational Applications (NLPTEA2016)

This paper presents the NLP-TEA 2016 shared task for Chinese grammatical error diagnosis which seeks to identify grammatical error types and their range of occurrence within sentences written by learners of Chinese as foreign language. We describe the task definition, data preparation, performance metrics, and evaluation results. Of the 15 teams registered for this shared task, 9 teams developed the system and submitted a total of 36 runs. We expected this evaluation campaign could lead to the development of more advanced NLP techniques for educational applications, especially for Chinese error detection. All data sets with gold standards and scoring scripts are made publicly available to researchers.

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YZU-NLP Team at SemEval-2016 Task 4: Ordinal Sentiment Classification Using a Recurrent Convolutional Network
Yunchao He | Liang-Chih Yu | Chin-Sheng Yang | K. Robert Lai | Weiyi Liu
Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)

2015

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International Journal of Computational Linguistics & Chinese Language Processing, Volume 20, Number 1, June 2015-Special Issue on Chinese as a Foreign Language
Lung-Hao Lee | Liang-Chih Yu | Li-Ping Chang
International Journal of Computational Linguistics & Chinese Language Processing, Volume 20, Number 1, June 2015-Special Issue on Chinese as a Foreign Language

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Guest Editoral: Special Issue on Chinese as a Foreign Language
Lung-Hao Lee | Liang-Chih Yu | Li-Ping Chang
International Journal of Computational Linguistics & Chinese Language Processing, Volume 20, Number 1, June 2015-Special Issue on Chinese as a Foreign Language

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Proceedings of the Eighth SIGHAN Workshop on Chinese Language Processing
Liang-Chih Yu | Zhifang Sui | Yue Zhang | Vincent Ng
Proceedings of the Eighth SIGHAN Workshop on Chinese Language Processing

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Overview of the NLP-TEA 2015 Shared Task for Chinese Grammatical Error Diagnosis
Lung-Hao Lee | Liang-Chih Yu | Li-Ping Chang
Proceedings of the 2nd Workshop on Natural Language Processing Techniques for Educational Applications

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Predicting Valence-Arousal Ratings of Words Using a Weighted Graph Method
Liang-Chih Yu | Jin Wang | K. Robert Lai | Xue-jie Zhang
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)

2014

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Overview of SIGHAN 2014 Bake-off for Chinese Spelling Check
Liang-Chih Yu | Lung-Hao Lee | Yuen-Hsien Tseng | Hsin-Hsi Chen
Proceedings of The Third CIPS-SIGHAN Joint Conference on Chinese Language Processing

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Identifying Emotion Labels from Psychiatric Social Texts Using Independent Component Analysis
Liang-Chih Yu | Chun-Yuan Ho
Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers

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A Sentence Judgment System for Grammatical Error Detection
Lung-Hao Lee | Liang-Chih Yu | Kuei-Ching Lee | Yuen-Hsien Tseng | Li-Ping Chang | Hsin-Hsi Chen
Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: System Demonstrations

2013

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Proceedings of the Seventh SIGHAN Workshop on Chinese Language Processing
Liang-Chih Yu | Yuen-Hsien Tseng | Jingbo Zhu | Fuji Ren
Proceedings of the Seventh SIGHAN Workshop on Chinese Language Processing

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Candidate Scoring Using Web-Based Measure for Chinese Spelling Error Correction
Liang-Chih Yu | Chao-Hong Liu | Chung-Hsien Wu
Proceedings of the Seventh SIGHAN Workshop on Chinese Language Processing

2012

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A Language Modeling Approach to Identifying Code-Switched Sentences and Words
Liang-Chih Yu | Wei-Cheng He | Wei-Nan Chien
Proceedings of the Second CIPS-SIGHAN Joint Conference on Chinese Language Processing

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Traditional Chinese Parsing Evaluation at SIGHAN Bake-offs 2012
Yuen-Hsien Tseng | Lung-Hao Lee | Liang-Chih Yu
Proceedings of the Second CIPS-SIGHAN Joint Conference on Chinese Language Processing

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Developing and Evaluating a Computer-Assisted Near-Synonym Learning System
Liang-Chih Yu | Kai-Hsiang Hsu
Proceedings of COLING 2012: Demonstration Papers

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Proceedings of the 24th Conference on Computational Linguistics and Speech Processing (ROCLING 2012)
Richard Tzong-Han Tsai | Liang-Chih Yu
Proceedings of the 24th Conference on Computational Linguistics and Speech Processing (ROCLING 2012)

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應用跳脫語言模型於同義詞取代之研究 (Skip N-gram Modeling for Near-Synonym Choice) [In Chinese]
Shih-Ting Chen | Wei-Cheng He | Philips Kokoh Prasetyo | Liang-Chih Yu
Proceedings of the 24th Conference on Computational Linguistics and Speech Processing (ROCLING 2012)

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International Journal of Computational Linguistics & Chinese Language Processing, Volume 17, Number 2, June 2012-Specia Issue on Selected Papers from ROCLING XXIII
Liang-Chih Yu | Wei-Ho Tsai
International Journal of Computational Linguistics & Chinese Language Processing, Volume 17, Number 2, June 2012-Specia Issue on Selected Papers from ROCLING XXIII

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International Journal of Computational Linguistics & Chinese Language Processing, Volume 17, Number 4, December 2012-Special Issue on Selected Papers from ROCLING XXIV
Liang-Chih Yu | Richard Tzong-Han Tsai | Chia-Ping Chen | Cheng-Zen Yang | Shu-Kai Hsieh
International Journal of Computational Linguistics & Chinese Language Processing, Volume 17, Number 4, December 2012-Special Issue on Selected Papers from ROCLING XXIV

2011

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A Baseline System for Chinese Near-Synonym Choice
Liang-Chih Yu | Wei-Nan Chien | Shih-Ting Chen
Proceedings of 5th International Joint Conference on Natural Language Processing

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Proceedings of the 23rd Conference on Computational Linguistics and Speech Processing (ROCLING 2011)
Wei-Ho Tsai | Liang-Chih Yu
Proceedings of the 23rd Conference on Computational Linguistics and Speech Processing (ROCLING 2011)

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多語語碼轉換之未知詞擷取 (Unknown Word Extraction from Multilingual Code-Switching Sentences) [In Chinese]
Yi-Lun Wu | Chaio-Wen Hsieh | Wei-Hsuan Lin | Chun-Yi Liu | Liang-Chih Yu
ROCLING 2011 Poster Papers

2010

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Discriminative Training for Near-Synonym Substitution
Liang-Chih Yu | Hsiu-Min Shih | Yu-Ling Lai | Jui-Feng Yeh | Chung-Hsien Wu
Proceedings of the 23rd International Conference on Computational Linguistics (Coling 2010)

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Word Sense Disambiguation Using Multiple Contextual Features
Liang-Chih Yu | Chung-Hsien Wu | Jui-Feng Yeh
International Journal of Computational Linguistics & Chinese Language Processing, Volume 15, Number 3-4, September/December 2010

2009

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Mining Association Language Patterns for Negative Life Event Classification
Liang-Chih Yu | Chien-Lung Chan | Chung-Hsien Wu | Chao-Cheng Lin
Proceedings of the ACL-IJCNLP 2009 Conference Short Papers

2008

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Corpus Cleanup of Mistaken Agreement Using Word Sense Disambiguation
Liang-Chih Yu | Chung-Hsien Wu | Jui-Feng Yeh | Eduard Hovy
International Journal of Computational Linguistics & Chinese Language Processing, Volume 13, Number 4, December 2008

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OntoNotes: Corpus Cleanup of Mistaken Agreement Using Word Sense Disambiguation
Liang-Chih Yu | Chung-Hsien Wu | Eduard Hovy
Proceedings of the 22nd International Conference on Computational Linguistics (Coling 2008)

2007

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Topic Analysis for Psychiatric Document Retrieval
Liang-Chih Yu | Chung-Hsien Wu | Chin-Yew Lin | Eduard Hovy | Chia-Ling Lin
Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics

2006

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HAL-Based Cascaded Model for Variable-Length Semantic Pattern Induction from Psychiatry Web Resources
Liang-Chih Yu | Chung-Hsien Wu | Fong-Lin Jang
Proceedings of the COLING/ACL 2006 Main Conference Poster Sessions

2005

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Automated Alignment and Extraction of a Bilingual Ontology for Cross-Language Domain-Specific Applications
Jui-Feng Yeh | Chung-Hsien Wu | Ming-Jun Chen | Liang-Chih Yu
International Journal of Computational Linguistics & Chinese Language Processing, Volume 10, Number 1, March 2005

2004

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Automated Alignment and Extraction of Bilingual Domain Ontology for Cross-Language Domain-Specific Applications
Jui-Feng Yeh | Chung-Hsien Wu | Ming-Jun Chen | Liang-Chih Yu
COLING 2004: Proceedings of the 20th International Conference on Computational Linguistics

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Automated Alignment and Extraction of Bilingual Domain Ontology for Medical Domain Web Search
Jui-Feng Yeh | Chung-Hsien Wu | Ming-Jun Chen | Liang-chih Yu
Proceedings of the Third SIGHAN Workshop on Chinese Language Processing