Yunxiao Zhou

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2018

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ECNU at SemEval-2018 Task 10: Evaluating Simple but Effective Features on Machine Learning Methods for Semantic Difference Detection
Yunxiao Zhou | Man Lan | Yuanbin Wu
Proceedings of the 12th International Workshop on Semantic Evaluation

This paper describes the system we submitted to Task 10 (Capturing Discriminative Attributes) in SemEval 2018. Given a triple (word1, word2, attribute), this task is to predict whether it exemplifies a semantic difference or not. We design and investigate several word embedding features, PMI features and WordNet features together with supervised machine learning methods to address this task. Officially released results show that our system ranks above average.

2017

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ECNU at SemEval-2017 Task 4: Evaluating Effective Features on Machine Learning Methods for Twitter Message Polarity Classification
Yunxiao Zhou | Man Lan | Yuanbin Wu
Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)

This paper reports our submission to subtask A of task 4 (Sentiment Analysis in Twitter, SAT) in SemEval 2017, i.e., Message Polarity Classification. We investigated several traditional Natural Language Processing (NLP) features, domain specific features and word embedding features together with supervised machine learning methods to address this task. Officially released results showed that our system ranked above average.

2016

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ECNU at SemEval-2016 Task 4: An Empirical Investigation of Traditional NLP Features and Word Embedding Features for Sentence-level and Topic-level Sentiment Analysis in Twitter
Yunxiao Zhou | Zhihua Zhang | Man Lan
Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)

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