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Cited 14 time in webofscience Cited 16 time in scopus
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Semantic optimization of query transformation in a large-scale peer-to-peer network

Authors
Jung, Jason J.
Issue Date
Jul-2012
Publisher
ELSEVIER SCIENCE BV
Keywords
Collective intelligence; Tag matching; Query transformation; Semantic peer-to-peer networks
Citation
NEUROCOMPUTING, v.88, pp 36 - 41
Pages
6
Journal Title
NEUROCOMPUTING
Volume
88
Start Page
36
End Page
41
URI
https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/37730
DOI
10.1016/j.neucom.2011.08.028
ISSN
0925-2312
Abstract
Ontologies have an important role in supporting efficient interoperability among information systems in distributed environment. In this paper, I propose a query transformation method to efficiently collect as many relevant resources from the distributed information systems (e.g., peer-to-peer network) as possible. More importantly, I consider a composite query which contains multiple semantics. The composite query from the source peer can be decomposed and propagated as maintaining the original contexts. Through the experiments, I have shown that query-activated concept (QAC)-based schemes have fulfilled an efficient query decomposition process on semantic peer-to-peer networks. (C) 2012 Elsevier B.V. All rights reserved.
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Jung, Jason J.
소프트웨어대학 (소프트웨어학부)
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