@inbook{2a0b8f6f3dbd4cd9b163ff2691ebfae1,
title = "A deep learning approach for question answering over knowledge base",
abstract = "With the increase of the scale of the knowledge base, it{\textquoteright}s important to answer question over knowledge base. In this paper, we will introduce a method to extract answers from Chinese knowledge base for Chinese questions. Our method uses a classifier to judge whether the relation in the triple is what the question asked, question-relation pairs are used to train the classifier. It{\textquoteright}s difficult to identify the right relation, so we find out the focus of the question and leverage the resource of lexical paraphrase in the preprocessing of the question. And the use of lexical paraphrase also can alleviate the out of vocabulary (OOV) problem. In order to let the right answer at the top of candidate answers, we present a ranking method to rank these candidate answers. The result of the final evaluation shows that our method achieves a good result.",
author = "Linjie Wang and Yu Zhang and Ting Liu",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2016.",
year = "2016",
month = dec,
day = "1",
doi = "10.1007/978-3-319-50496-4\_82",
language = "英语",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "885--892",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
address = "德国",
}