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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Collections - College of Software > School of Computer Science and Engineering > 1. Journal Articles
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