DocumentCode :
1804973
Title :
Using Data-Extraction Ontologies to Foster Automating Semantic Annotation
Author :
Ding, Yihong ; Embley, David W.
Author_Institution :
Brigham Young University
fYear :
2006
fDate :
2006
Abstract :
Semantic annotation adds formal metadata to web pages to link web data with ontology concepts. Automated semantic annotation is a primary way of enabling the semantic web. A main drawback of existing automated semantic annotation approaches is that they need a post-extraction mapping between extraction categories and ontology concepts. This mapping requirement usually needs human intervention, which decreases automation. Our approach uses data-extraction ontologies to avoid this problem. To automate semantic annotation, the new approach uses an ontology-based data recognizer that fosters automated semantic annotation, optimizes the system performance, provides support for ontology assembly, and is compatible with semantic web standards.
Keywords :
Assembly systems; Automation; Computer science; Data mining; Engines; Humans; Object oriented modeling; Ontologies; Semantic Web; Web pages;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Engineering Workshops, 2006. Proceedings. 22nd International Conference on
Conference_Location :
Atlanta, GA, USA
Print_ISBN :
0-7695-2571-7
Type :
conf
DOI :
10.1109/ICDEW.2006.158
Filename :
1623934
Link To Document :
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