EDUTELLA: a P2P networking infrastructure based on RDF
Proceedings of the 11th international conference on World Wide Web
Intelligent Manufacturing: Programming Environments for CIM
Intelligent Manufacturing: Programming Environments for CIM
Determining Semantic Similarity among Entity Classes from Different Ontologies
IEEE Transactions on Knowledge and Data Engineering
An Information-Theoretic Definition of Similarity
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Peer-to-peer information retrieval using self-organizing semantic overlay networks
Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
HELIOS: a General Framework for Ontology-based Knowledge Sharing and Evolution in P2P Systems
DEXA '03 Proceedings of the 14th International Workshop on Database and Expert Systems Applications
Remindin': semantic query routing in peer-to-peer networks based on social metaphors
Proceedings of the 13th international conference on World Wide Web
RDFPeers: a scalable distributed RDF repository based on a structured peer-to-peer network
Proceedings of the 13th international conference on World Wide Web
Linked: How Everything Is Connected to Everything Else and What It Means
Linked: How Everything Is Connected to Everything Else and What It Means
A Semantics-based Approach to Large-Scale Mobile Social Networking
Mobile Networks and Applications
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Locating desirable resources and information from a large-scale distributed system such as P2P system and grid is a very important issue. However, the distributed, heterogeneous, and unstructured nature of the system makes this issue very challenging. In this paper, we propose Self-Organized Overlay Network (SOON), an unstructured P2P overlay architecture, to facilitate sharing and searching semantically heterogeneous contents. In particular, we have proposed a semantics-aware topology construction method to group nodes sharing similar semantics together to create small-worlds. For this purpose, we have designed an algorithm to extract a node's ontology summary and use that summary to compute the semantic similarity between nodes. With this semantic similarity defined, nodes are grouped accordingly, forming semantic virtual domains and clusters. Resource information integration and searching can be efficiently performed on top of this topology.