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