Bo Peng


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YNU-HPCC at SemEval-2018 Task 3: Ensemble Neural Network Models for Irony Detection on Twitter
Bo Peng | Jin Wang | Xuejie Zhang
Proceedings of The 12th International Workshop on Semantic Evaluation

This paper describe the system we proposed to participate the first year of Irony detection in English tweets competition. Previous works demonstrate that LSTMs models have achieved remarkable performance in natural language processing; besides, combining multiple classification from various individual classifiers in general is more powerful than a single classification. In order to obtain more precision classification of irony detection, our system trained several individual neural network classifiers and combined their results according to the ensemble-learning algorithm.


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Chinese Grammatical Error Diagnosis Using Single Word Embedding
Jinnan Yang | Bo Peng | Jin Wang | Jixian Zhang | Xuejie Zhang
Proceedings of the 3rd Workshop on Natural Language Processing Techniques for Educational Applications (NLPTEA2016)

Abstract Automatic grammatical error detection for Chinese has been a big challenge for NLP researchers. Due to the formal and strict grammar rules in Chinese, it is hard for foreign students to master Chinese. A computer-assisted learning tool which can automatically detect and correct Chinese grammatical errors is necessary for those foreign students. Some of the previous works have sought to identify Chinese grammatical errors using template- and learning-based methods. In contrast, this study introduced convolutional neural network (CNN) and long-short term memory (LSTM) for the shared task of Chinese Grammatical Error Diagnosis (CGED). Different from traditional word-based embedding, single word embedding was used as input of CNN and LSTM. The proposed single word embedding can capture both semantic and syntactic information to detect those four type grammatical error. In experimental evaluation, the recall and f1-score of our submitted results Run1 of the TOCFL testing data ranked the fourth place in all submissions in detection-level.


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WordTopic-MultiRank: A New Method for Automatic Keyphrase Extraction
Fan Zhang | Lian’en Huang | Bo Peng
Proceedings of the Sixth International Joint Conference on Natural Language Processing