@inproceedings{0a583fee04df4e19ae92ca516adbb49f,
title = "Singleton detection for coreference resolution via multi-window and multi-filter CNN",
abstract = "Mention detection is the first and a key stage in most of coreference resolution systems. Singleton mentions are the ones which appear only once and are not mentioned in the following texts. Singleton mentions always affect the performance of coreference resolution systems. To remove the singleton ones from the automatically predicted mentions, we propose a novel singleton detection method based on multi-window and multi-filter convolutional neural network (MMCNN). The MMCNN model can detect singleton mentions with less use of hand-designed features and more sentence information. Experiments show that our system outperforms all the existing singleton detection systems.",
keywords = "Convolutional neural network, Coreference resolution, Singleton detection",
author = "Kenan Li and Heyan Huang and Yuhang Guo and Ping Jian",
note = "Publisher Copyright: {\textcopyright} Springer Nature Singapore Pte Ltd. 2017.; 13th China Workshop on Machine Translation, CWMT 2017 ; Conference date: 27-09-2017 Through 29-09-2017",
year = "2017",
doi = "10.1007/978-981-10-7134-8\_2",
language = "English",
isbn = "9789811071331",
series = "Communications in Computer and Information Science",
publisher = "Springer Verlag",
pages = "9--19",
editor = "Wong, \{Derek F.\} and Deyi Xiong",
booktitle = "Machine Translation - 13th China Workshop, CWMT 2017, Revised Selected Papers",
address = "Germany",
}