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|ErsterAutorNachname=Maedche
|Author=Alexander Maedche
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|Abstract=Automatic intelligent web exploration will benefit from shallow information extraction techniques if the latter can be brought to work within many different domains. The major bottleneck for this, however, lies in the so far difficult and expensive modeling of lexical knowledge, extraction rules, and an ontology that together define the information extraction system. In this paper we present a bootstrapping approach that allows for the fast creation of an ontology-based information extracting system relying on several basic components, viz. a core information extraction system, an ontology engineering environment and an inference engine. We make extensive use of machine learning techniques to support the semi-automatic, incremental bootstrapping of the domain-specific target information extraction system
 
|Abstract=Automatic intelligent web exploration will benefit from shallow information extraction techniques if the latter can be brought to work within many different domains. The major bottleneck for this, however, lies in the so far difficult and expensive modeling of lexical knowledge, extraction rules, and an ontology that together define the information extraction system. In this paper we present a bootstrapping approach that allows for the fast creation of an ontology-based information extracting system relying on several basic components, viz. a core information extraction system, an ontology engineering environment and an inference engine. We make extensive use of machine learning techniques to support the semi-automatic, incremental bootstrapping of the domain-specific target information extraction system
 
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|Download=2001_495_Maedche_Bootstrapping a_1.pdf
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|Download=2001_495_Maedche_Bootstrapping_a_1.pdf
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Aktuelle Version vom 16. Oktober 2009, 17:19 Uhr


Bootstrapping an Ontology-based Information Extraction System




Veröffentlicht: 2001
Herausgeber: P. Szczepaniak, J. Segovia, J. Kacprzyk, L. Zadeh
Buchtitel: Intelligent Exploration of the Web
Verlag: Springer / Physica Verlag, Heidelberg
BibTeX

Kurzfassung
Automatic intelligent web exploration will benefit from shallow information extraction techniques if the latter can be brought to work within many different domains. The major bottleneck for this, however, lies in the so far difficult and expensive modeling of lexical knowledge, extraction rules, and an ontology that together define the information extraction system. In this paper we present a bootstrapping approach that allows for the fast creation of an ontology-based information extracting system relying on several basic components, viz. a core information extraction system, an ontology engineering environment and an inference engine. We make extensive use of machine learning techniques to support the semi-automatic, incremental bootstrapping of the domain-specific target information extraction system

Download: Media:2001_495_Maedche_Bootstrapping_a_1.pdf



Forschungsgruppe

Wissensmanagement


Forschungsgebiet