Space/time trade-offs in hash coding with allowable errors
Communications of the ACM
Chord: A scalable peer-to-peer lookup service for internet applications
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
A scalable content-addressable network
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
Pastry: Scalable, Decentralized Object Location, and Routing for Large-Scale Peer-to-Peer Systems
Middleware '01 Proceedings of the IFIP/ACM International Conference on Distributed Systems Platforms Heidelberg
PlanetP: Using Gossiping to Build Content Addressable Peer-to-Peer Information Sharing Communities
HPDC '03 Proceedings of the 12th IEEE International Symposium on High Performance Distributed Computing
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
An Adaptive Protocol for Efficient Support of Range Queries in DHT-Based Systems
ICNP '04 Proceedings of the 12th IEEE International Conference on Network Protocols
Similarity Searching in Peer-to-Peer Databases
ICDCS '05 Proceedings of the 25th IEEE International Conference on Distributed Computing Systems
International Journal of Metadata, Semantics and Ontologies
International Journal of Metadata, Semantics and Ontologies
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In structured Peer-to-Peer (P2P) overlay networks, similar documents are randomly distributed over peers with their data identifiers consistently hashed, which makes complex search challenging. Current state-of-the-art complex query approaches in structured P2P systems are mainly based on inverted list intersection. When the identifiers are distributed among peers, a complex query may involve many peers and cause a large amount of network traffic. One solution of implementing efficient complex query is to organize documents on each peer using clustering. In this paper, we propose a clustering method, QBC, which is composed of Pull Mode and Push Mode. Pull Mode uses historical queries to direct clustering in structured P2P overlay networks and Push Mode applies modified Vector Space Model (VSM) to define document set on each peer in order to assist clustering. Experiments show that QBC can reduce the number of peers visited during complex search, hence both query response time and network traffic are decreased.