@inproceedings{14e85e25b5bd4e0ca2124e9134b9d1a8,
title = "Combine multi-features with deep learning for answer selection",
abstract = "Answer selection is an important subtask in open-domain question answering (QA) system, which mainly models for question and answer pairs. In this paper, we first develop a basic framework based on bidirectional long short term memory (Bi-LSTM), and then we extract lexical and topic features in question and answer respectively, finally, we append these features to Bi-LSTM models. Our models experiment on WikiQA dataset, Experimental results show that our models get a slight improvement compared to other published state of the art results.",
keywords = "Bi-LSTM, QA, answer selection, multifeatures",
author = "Yuqing Zheng and Chenghe Zhang and Dequan Zheng and Feng Yu",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 21st International Conference on Asian Language Processing, IALP 2017 ; Conference date: 05-12-2017 Through 07-12-2017",
year = "2017",
month = jul,
day = "2",
doi = "10.1109/IALP.2017.8300553",
language = "英语",
series = "Proceedings of the 2017 International Conference on Asian Language Processing, IALP 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "91--94",
editor = "Rong Tong and Yue Zhang and Yanfeng Lu and Minghui Dong",
booktitle = "Proceedings of the 2017 International Conference on Asian Language Processing, IALP 2017",
address = "美国",
}