Large-Scale Pattern-Based Information Extraction from the World Wide Web

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https://www.ksp.kit.edu/9783866444799
Author(s)
Blohm, Sebastian
Language
English
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Abstract
Extracting information from text is the task of obtaining structured, machine-processable facts from information that is mentioned in an unstructured manner. It thus allows systems to automatically aggregate information for further analysis, efficient retrieval, automatic validation, or appropriate visualization. This work explores the potential of using textual patterns for Information Extraction from the World Wide Web.
URI
https://directory.doabooks.org/handle/20.500.12854/51420
Keywords
Information Extraction; Data Mining; Pattern Induction; Web Mining; Machine Learning
DOI
10.5445/KSP/1000015694
ISBN
9783866444799
Publisher
KIT Scientific Publishing
Publisher website
http://www.ksp.kit.edu/
Publication date and place
2010
Classification
Business strategy
Pages
VII, 236 p.
Review type
Full text
Anonymity
All identities known
Reviewer type
Internal editor; External peer reviewer
Review stage
Pre-publication
Open review
No
Publish responsibility
Scientific or Editorial Board
Rights
https://creativecommons.org/licenses/by-nc-nd/4.0/
https://creativecommons.org/licenses/by-nc-nd/4.0/
Except where otherwise noted, this item's license is described as https://creativecommons.org/licenses/by-nc-nd/4.0/