Abstract
The Semantic Web is envisioned as the next generation web in which data instances are enriched with metadata defined in ontologies to describe the meaning of its instances. In this paper, we present an approach that exploits ontologies in guiding the change detection to their data instances. Inference rules are identified based on the semantic relationships among concepts, properties and instances as well as their change behaviors. Starting with changes to some seed instances, a reasoning engine is designed to fire the pre-defined rule set and act on ontologies to project some semantically associated concepts as target concepts. Certain instances of these target concepts are further selected as target instances, which have a high likelihood of having changed. Our approach is specifically oriented toward the Semantic Web, thus it has intelligence to exploit the semantic associations among data instances and make smart decisions.
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Qin, L., Atluri, V. (2004). Ontology-Guided Change Detection to the Semantic Web Data. In: Atzeni, P., Chu, W., Lu, H., Zhou, S., Ling, TW. (eds) Conceptual Modeling – ER 2004. ER 2004. Lecture Notes in Computer Science, vol 3288. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30464-7_47
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DOI: https://doi.org/10.1007/978-3-540-30464-7_47
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23723-5
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