大規模語彙知識に基づく連想情報を用いた談話関係認識

Tohoku University乾健太

Connective prediction using machine learning for implicit discourse relation classification

10.1109/IJCNN.2012.6252548Proceedings of the International Joint Conference on Neural Networks85OF

Connective Prediction using Machine Learning for Implicit Discourse Relation Classification

Abstract—Implicit discourse relation classification is a challenge task due to missing discourse connective. Some work directly adopted machine learning algorithms and linguistically informed features to address this task. However, one interesting solution is to automatically predict implicit discourse connective. In this paper, we present a novel two-step machine learningbased approach to implicit discourse relation classification. We first use machine learning method to automatically predict the discourse connective that can best express the implicit discourse relation. Then the predicted implicit discourse connective is used to classify the implicit discourse relation. Experiments on Penn Discourse Treebank 2.0 (PDTB) and Biomedical Discourse Relation Bank (BioDRB) show that our method performs better than the baseline system and previous work. I