Improving short-text representation in convolutional networks by dependency parsing
文献类型：期刊论文
| 作者 | Zhang, Siheng ; Zhang, Wensheng; Niu, Jinghao
|
| 刊名 | KNOWLEDGE AND INFORMATION SYSTEMS
 |
| 出版日期 | 2019-10-01 |
| 卷号 | 61期号:1页码:463-484 |
| ISSN号 | 0219-1377 |
| 关键词 | Convolutional neural network Dependency parsing Question answering system Question classification Semantic equivalence |
| DOI | 10.1007/s10115-018-1312-9 |
| 通讯作者 | Zhang, Wensheng(zhangwenshengia@hotmail.com) |
| 英文摘要 | Automatic question answering (QA) system is the inevitable trend of future search engines. As the essential steps of QA, question classification and text retrieval both require algorithms to capture the semantic information and syntactic structure of natural language. This paper proposes dependency-based convolutional networks to learn a representation of sentences. First, we use dependency layer to map discrete word depth on the dependency tree of a sentence into continuous real space. Then, the mapping result serves as weight of word vectors and convolutional kernels are employed as feature extractors for further specific tasks. The method proposed allows convolutional networks to take the advantage of higher representational ability of dependency structure. Experiments involving three tasks including text classification, duplicate classification and text pairs ranking confirm the advantages of our model. |
| WOS关键词 | GENERIC CLINICAL QUESTIONS ; TAXONOMY |
| 资助项目 | National Natural Science Foundation of China[U1636220] ; National Natural Science Foundation of China[61432008] ; National Natural Science Foundation of China[61472423] ; Huawei Innovation Research Program[HO2017050001BI] ; Beijing Natural Science Foundation[4172063] |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| 出版者 | SPRINGER LONDON LTD |
| WOS记录号 | WOS:000483698200017 |
| 资助机构 | National Natural Science Foundation of China ; Huawei Innovation Research Program ; Beijing Natural Science Foundation |
| 源URL | [http://ir.ia.ac.cn/handle/173211/27229]  |
| 专题 | 精密感知与控制研究中心_人工智能与机器学习 |
| 通讯作者 | Zhang, Wensheng |
| 作者单位 | Univ Chinese Acad Sci, Sch Comp & Control Engn, Inst Automat, Chinese Acad Sci, 95 Zhongguancun East Rd, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Siheng,Zhang, Wensheng,Niu, Jinghao. Improving short-text representation in convolutional networks by dependency parsing[J]. KNOWLEDGE AND INFORMATION SYSTEMS,2019,61(1):463-484. |
| APA | Zhang, Siheng,Zhang, Wensheng,&Niu, Jinghao.(2019).Improving short-text representation in convolutional networks by dependency parsing.KNOWLEDGE AND INFORMATION SYSTEMS,61(1),463-484. |
| MLA | Zhang, Siheng,et al."Improving short-text representation in convolutional networks by dependency parsing".KNOWLEDGE AND INFORMATION SYSTEMS 61.1(2019):463-484. |
入库方式： OAI收割
来源：自动化研究所
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