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New Technology of Library and Information Service  2004, Vol. 20 Issue (6): 1-5    DOI: 10.11925/infotech.1003-3513.2004.06.01
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Information Extraction and Its Functions in the Digital Library
Zhang Zhixiong
(Library of Chinese Academy of Science, Beijing 100080, China)
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Information Extraction (IE) is a term which has come to be applied to the activity of automatically extracting pre-specified sorts of information from natural language texts. This paper analyses the basic concept of information extraction, the main research activities on information extraction, the type of information extraction and the system of information extraction. The author believes information extraction will play a very important role in coping with the huge collection of digital information. It can provide helps in automat ic annotation of digital materials, automatic acquisition of metadata, improving data mining in information analysis, developing knowledge base from free text, and generating answers in digital reference system.

Key wordsInformation Extraction(IE)      Message understanding conference      Digital library      Natural language processing     
Received: 08 March 2004      Published: 25 June 2004


Corresponding Authors: Zhang Zhixiong     E-mail:
About author:: Zhang Zhixiong

Cite this article:

Zhang Zhixiong. Information Extraction and Its Functions in the Digital Library. New Technology of Library and Information Service, 2004, 20(6): 1-5.

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1  Andrew Joscelyne and Rose Lockwood,EUROMAP Final Report: BenchmarkingHLTprogressinEurope-FullReport.,2004)
2  Gate Information Extraction, Feb.8,2004)
3  NLP group of University of Sheffield,Information Extraction. Feb.8,2004)
4  Douglas E.Appeltand DavidJ.Israel,Introduction to Informa
tion Extraction.Technology, Feb.8,2004)
5  Donna Harman,Whatis Information Extraction? Feb.8,2004)
6  Hamish Cunningham,Information Extraction-a User Guide(SecondEdition), Feb.8,2004)
7  RALI,Bilingual Information Extraction, Feb.8,2004)
8  Jakub Piskorski&FeiyuXu,Overview of MUC and Introduction to Text Mining, Feb.8,2004)
9  Nancy A.Chinchor,OVERVIEWOFMUC-7/MET , Feb.
10  E.Marsh&D.Perzanowski,MUC-7EVALUATION OF IE TECHNOLOGY:Overviewofresults, Feb.8,2004)
11  ACE-Automatic Content Extraction, Feb.8,2004)
12  Diana Maynard,Kalina Bontcheva,Hamish Cunningham,To wards a semantic extraction of named entities,In Proceedings Recent Advances in Natural,Borovets,Bulgaria,2003. Feb.8,2004)
13  H.Cunningham etc.,GATE:A framework and graphical development environment for robust NLP tools and applications,Proceedings of the 40th Anniversary Meeting of the Associationfor Computational Linguistics(2002). Feb.8,2004)
14  Valentin Tablan,GATE and Information Extraction, Feb.8,2004)
15  ANNIE. Feb.8,2004)
16  Kalina Bontchevaetc.,Using Human Language Technology for Automatic Annotation and Indexing of Digital Library Content.Proceedings of the 6th European Conference on Research and Advanced Technology for Digital Libraries(ECDL’2002),Rome, September2002. Feb.8,2004)
17  Reinoso-Castillo,J.(2002).Ontolgy-Driven Information Extraction and Integration from Autonomous ,Heterogeneous,Distributed Data Sources--AFederatedQuery-Centric Approach.Masters Thesis.Artificial Intelligence Research Laboratory.Department of Computer Science.Iowa State University
(Accessed Feb.8,2004)
18  Vasant Honavaretc.,Ontology-Driven Information Extraction and Knowledge Acquisition from Heterogeneous,Distributed,Autonomous Biological Data Sources.,2004)
19  Roazhon,Information Extraction:from unstructured texts to knowledge bases, Feb.8,2004)
20  Rohini Srihariand WeiLi,Information Extraction Supported Question Answering. Feb.8,2004)

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