Management system for OWL documents in distributed environment on the semantic Web
- Authors
- Kim, YounHee; Kim, YongWook; Kim, ByungGon; Lim, HaeChull
- Issue Date
- 2007
- Publisher
- IEEE
- Keywords
- OWL; distributed ontology; storage; index
- Citation
- 9TH INTERNATIONAL CONFERENCE ON ADVANCED COMMUNICATION TECHNOLOGY: TOWARD NETWORK INNOVATION BEYOND EVOLUTION, VOLS 1-3, pp.1216 - +
- Journal Title
- 9TH INTERNATIONAL CONFERENCE ON ADVANCED COMMUNICATION TECHNOLOGY: TOWARD NETWORK INNOVATION BEYOND EVOLUTION, VOLS 1-3
- Start Page
- 1216
- End Page
- +
- URI
- https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/29942
- DOI
- 10.1109/ICACT.2007.358577
- Abstract
- In the current Web, it is not possible to manage information resources manually and intelligently. And most users prefer more accurate information. To overcome these limitations of the current Web, the Semantic Web was conceived. Unlike the current Web, in the Semantic Web, metadata and ontology will play important roles for advanced information retrieval systems. For describing semantics and reasoning about information resources on the Web, RDF, RDF Schema and OWL are proposed by W3C. OWL has rich expressive power and is considered as the next standard language for describing metadata and ontology. The related information resources are placed in distributed systems on the Web. So, for providing seamless services without the awareness of far distance, efficient management of the distributed information resources is required. And to be provided with richer query results, people need to acquire related information through integrating the distributed ontologies. Among languages for describing metadata and ontology, only OWL can support dispersibility of Web. In this paper, first we classify features of OWL for supporting distributed environment on the Web and propose strategies for united query processing of the distributed ontologies. Secondly, we suggest methods of storing ontologies according to the proposed strategies. Finally, we propose an indexing method to improve query answering performance.
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Collections - College of Engineering > Computer Engineering Major > 1. Journal Articles
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