Please wait a minute...
New Technology of Library and Information Service  2007, Vol. 2 Issue (10): 38-41    DOI: 10.11925/infotech.1003-3513.2007.10.09
Current Issue | Archive | Adv Search |
Architecture of Knowledge Extraction Based on NLP
Hua Bolin
(Institute of Scientific and Technical Information of China, Beijing 100038,China)
Download: PDF(547 KB)   HTML  
Export: BibTeX | EndNote (RIS)      
Abstract  

Based on the studies of system architecture of NLP platform and knowledge extraction system, the author brings forth a detailed resolution on how to design a knowledge extraction system based on NLP. NLP technique includes eight modules, such as segmentation, part-of speech tag, syntactic analysis and semantic analysis. Knowledge extraction includes four modules, such as documents type analysis, discourse analysis, knowledge extraction and knowledge representation. Research on system architecture of knowledge extraction based on NLP is beneficial to not only find relations between NLP and knowledge extraction, but also analyze system flow and critical technology of knowledge extraction.
Key words： Natural Language Processing(NLP)      Knowledge extraction      Document analysis      Content analysis      System architecture      Critical technology     
Received: 04 July 2007      Published: 25 October 2007
: 

G35 

 
     
  TP391

 		 
Corresponding Authors: Hua Bolin     E-mail: huabolin@istic.ac.cn
About author:: Hua Bolin
Service
E-mail this article
Add to my bookshelf
Add to citation manager
E-mail Alert
RSS
Articles by authors

Cite this article:

Hua Bolin. Architecture of Knowledge Extraction Based on NLP. New Technology of Library and Information Service, 2007, 2(10): 38-41.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2007.10.09     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2007/V2/I10/38

［1］ Jionghua Ji.Semi-automatic Ontology-based Knowledge Extraction and Verification From Unstructured Document［D］. State University System of Florida,2000
［2］ Von-Wun Soo, Hsiang-Yuen Yeh, Shih-Neng Lin,et al.Ontology-based Knowledge Extraction from Semantic Annotated Biological Literature［C］The Ninth Conference on Artificial Intelligence and Applications, 2004
［3］ 化柏林，赵亮．知识抽取中的嵌套向量分词技术［J］．现代图书情报技术，2007(7)：50-53
［4］ 刘开瑛．中文文本自动分词和标注［M］．北京：商务印书馆，2000
［5］ Brown P F,Della Pietra S A,Della Pietra V J,et al.Word-sense Disambiguation Using Statistical Methods［EB/OL］.［2007-07-05］http://acl.ldc.upenn.edu/P/P91/P91-1034.pdf
［6］ Yarowsky D. Decision List for Lexical Ambiguity Resolution:Application to Accent Restoration in Spanish and Freneh［C］.Proceedings of 32nd Annual Meeting of the Association for Computational Linguistics,Las Cruces,NM,1994
［7］ Kaplan,Ronald M. The Formal Architecture of Lexical-Functional Grammar［J］. Journal of Information Science and Engineering,1989,5：305-322.
［8］ Jean-Pierre Koenig. Book Reviews: Head-driven Phrase Structure Grammar and German in Head -driven Phrase Structure Grammar［EB/OL］.［2007-07-06］.http://acl.ldc.upenn.edu/J/J96/J96-1005.pdf
［9］ 温有奎，温浩，徐端颐，等．基于知识元的文本知识标引［J］．情报学报，2006（3）：282-288
［10］ John F.Sowa．知识表示（英文版）［M］．北京：机械工业出版社，2003
[1] Jing Shi,Chenlu Li,Yuxing Qian,Liqin Zhou,Bin Zhang. Information Needs of Domestic and International HCQA Users ——An Empirical Analysis[J]. 数据分析与知识发现, 2019, 3(5): 1-10.
[2] Hongxia Xu,Chunwang Li. Review of Knowledge Extraction of Scientific Literature[J]. 数据分析与知识发现, 2019, 3(3): 14-24.
[3] Ying Wang,Li Qian,Jing Xie,Zhijun Chang,Beibei Kong. Building Knowledge Graph with Sci-Tech Big Data[J]. 数据分析与知识发现, 2019, 3(1): 15-26.
[4] Cong Wu,Yuxiang Zhao,Qinghua Zhu. Analyzing Crowdfunding Videos Based on Task Presentation——Case Study of zhongchou.com[J]. 数据分析与知识发现, 2017, 1(10): 64-76.
[5] Jianhua Liu,Ying Wang,Zhixiong Zhang,Chuanxi Li. Extracting Semantic Knowledge from Plant Species Diversity Collections[J]. 数据分析与知识发现, 2017, 1(1): 37-46.
[6] Hua Bolin. Extracting Information Method Term from Chinese Academic Literature[J]. 现代图书情报技术, 2013, (6): 68-75.
[7] Huang Xiaobin, Zhong Huixin. Applying of Content Analysis Method in Business Online Advertising Intelligence Extraction ——Based on Advertising of China Three Telecom Operators[J]. 现代图书情报技术, 2012, 28(7): 90-95.
[8] Yang Rui, Tang Yijie, Liu Yi, Li Wei. Comprehensive Evaluation of the Ontology Building System in the Web Environment[J]. 现代图书情报技术, 2012, 28(1): 13-18.
[9] Yao Fei,Chen Wu,Zhao Yang. Architecture Design and Implementation of English Website of Tsinghua University Library[J]. 现代图书情报技术, 2009, 3(3): 91-95.
[10] Jiang Caihong,Qiao Xiaodong ,Zhu Lijun. Ontology-based Patent Abstracts' Knowledge Extraction[J]. 现代图书情报技术, 2009, 3(2): 23-28.
[11] Wu Zhenxin,Xiang Jing. Analysis of Retrieval System Architecture in Web Archive[J]. 现代图书情报技术, 2009, 3(1): 22-27.
[12] Zhang Zhixiong,Wu Zhenxin,Liu Jianhua,Xu Jian,Hong Na,Zhao Qi. Analysis of State-of-the-Art Knowledge Extraction Technologies[J]. 现代图书情报技术, 2008, 24(8): 2-11.
[13] Zhou Ning,Wang Miao. Research on Special Domain Oriented Knowledge Management Model Based on MUDs[J]. 现代图书情报技术, 2008, 24(5): 33-38.
[14] Wang Min,Zhang Zhiqiang. A Content Analysis of Knowledge Discovery Papers in Information Science and Library Science[J]. 现代图书情报技术, 2008, 24(2): 64-68.
[15] Hua Bolin. Stop-word Processing Technique in Knowledge Extraction[J]. 现代图书情报技术, 2007, 2(8): 48-51.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626，82624938   E-mail:jishu@mail.las.ac.cn