@inproceedings{00315ffc56c0460cb69ff8830b70c238,
title = "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 learning-based 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.",
author = "Yu Xu and Man Lan and Yue Lu and Niu, \{Zheng Yu\} and Tan, \{Chew Lim\}",
year = "2012",
doi = "10.1109/IJCNN.2012.6252548",
language = "英语",
isbn = "9781467314909",
series = "Proceedings of the International Joint Conference on Neural Networks",
booktitle = "2012 International Joint Conference on Neural Networks, IJCNN 2012",
note = "2012 Annual International Joint Conference on Neural Networks, IJCNN 2012, Part of the 2012 IEEE World Congress on Computational Intelligence, WCCI 2012 ; Conference date: 10-06-2012 Through 15-06-2012",
}