DocumentCode
741421
Title
Information Extraction
Author
Grishman, Ralph
Author_Institution
New York University
Volume
30
Issue
5
fYear
2015
Firstpage
8
Lastpage
15
Abstract
Much of the world´s knowledge is recorded in natural language text, but making effective use of it in this form poses a major challenge. Information extraction converts this knowledge to a structured form suitable for computer manipulation, opening up many possibilities for using it. In this review, the author describes the processing pipeline of information extraction, how the pipeline components are trained, and how this training can be made more efficient. He also describes some of the challenges that must be addressed for information extraction to become a more widely used technology.
Keywords
Chemistry; Databases; Hidden Markov models; Semantics; Syntactics; Tagging; Training; NLP; information extraction; intelligent systems; natural language processing;
fLanguage
English
Journal_Title
Intelligent Systems, IEEE
Publisher
ieee
ISSN
1541-1672
Type
jour
DOI
10.1109/MIS.2015.68
Filename
7243219
Link To Document