Associated Activation-Driven Enrichment: Understanding Implicit Information from a Cognitive Perspective
文献类型：期刊论文
| 作者 | Bai, Jie1,2 ; Li, Linjing1; Zeng, Daniel1,3; Li, Qiudan1
|
| 刊名 | IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
 |
| 出版日期 | 2017-12-01 |
| 卷号 | 29期号:12页码:2655-2668 |
| 关键词 | Text Analysis Knowledge Representation Cognitive Simulation Association Rules |
| DOI | 10.1109/TKDE.2017.2745565 |
| 文献子类 | Article |
| 英文摘要 | In this paper, we propose a novel text representation paradigm and a set of follow-up text representation models based on cognitive psychology theories. The intuition of our study is that the knowledge implied in a large collection of documents may improve the understanding of single documents. Based on cognitive psychology theories, we propose a general text enrichment framework, study the key factors to enable activation of implicit information, and develop new text representation methods to enrich text with the implicit information. Our study aims to mimic some aspects of human cognitive procedure in which given stimulant words serve to activate understanding implicit concepts. By incorporating human cognition into text representation, the proposed models advance existing studies by mining implicit information from given text and coordinating with most existing text representation approaches at the same time, which essentially bridges the gap between explicit and implicit information. Experiments on multiple tasks show that the implicit information activated by our proposed models matches human intuition and significantly improves the performance of the text mining tasks as well. |
| WOS关键词 | TEXT REPRESENTATION MODEL ; CLASSIFICATION |
| WOS研究方向 | Computer Science ; Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:000414712700003 |
| 资助机构 | National Key R&D Program of China(2016QY02D0205) ; National Natural Science Foundation of China(71202169 ; Chinese Academy of Sciences(ZDRW-XH-2017-3) ; SKLMCCS ; 71602184 ; 71621002 ; 61671450 ; U1435221) |
| 源URL | [http://ir.ia.ac.cn/handle/173211/19855]  |
| 专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_互联网大数据与安全信息学研究中心 |
| 作者单位 | 1.Chinese Acad Sci, State Key Lab Management & Control Complex Syst, Inst Automat, Beijing 100049, Peoples R China 2.Univ Chinese Acad Sci, Sch Comp & Control Engn, Beijing 100049, Peoples R China 3.Univ Arizona, Dept Management Informat Syst, Tucson, AZ 85721 USA |
| 推荐引用方式 GB/T 7714 | Bai, Jie,Li, Linjing,Zeng, Daniel,et al. Associated Activation-Driven Enrichment: Understanding Implicit Information from a Cognitive Perspective[J]. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING,2017,29(12):2655-2668. |
| APA | Bai, Jie,Li, Linjing,Zeng, Daniel,&Li, Qiudan.(2017).Associated Activation-Driven Enrichment: Understanding Implicit Information from a Cognitive Perspective.IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING,29(12),2655-2668. |
| MLA | Bai, Jie,et al."Associated Activation-Driven Enrichment: Understanding Implicit Information from a Cognitive Perspective".IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 29.12(2017):2655-2668. |
入库方式： OAI收割
来源：自动化研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。