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Using Data-Extraction Ontologies to Foster Automating Semantic Annotation
Yihong Ding D.W. Embley
Brigham Young University;

This paper appears in: Data Engineering Workshops, 2006. Proceedings. 22nd International Conference on
Publication Date: 2006
On page(s): x138-x138
Location: Atlanta, GA, USA,
ISBN: 0-7695-2571-7
Digital Object Identifier: 10.1109/ICDEW.2006.158
Current Version Published: 2006-04-24

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.

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