Combining fuzzy information from multiple systems
Journal of Computer and System Sciences
Distance browsing in spatial databases
ACM Transactions on Database Systems (TODS)
Chord: a scalable peer-to-peer lookup protocol for internet applications
IEEE/ACM Transactions on Networking (TON)
Efficient User-Adaptable Similarity Search in Large Multimedia Databases
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
An efficient nearest neighbor algorithm for P2P settings
dg.o '05 Proceedings of the 2005 national conference on Digital government research
M-Chord: a scalable distributed similarity search structure
InfoScale '06 Proceedings of the 1st international conference on Scalable information systems
On scalability of the similarity search in the world of peers
InfoScale '06 Proceedings of the 1st international conference on Scalable information systems
M-Grid: similarity searching in grid
P2PIR '06 Proceedings of the international workshop on Information retrieval in peer-to-peer networks
Nearest neighbor search in metric spaces through Content-Addressable Networks
Information Processing and Management: an International Journal
A content-addressable network for similarity search in metric spaces
DBISP2P'05/06 Proceedings of the 2005/2006 international conference on Databases, information systems, and peer-to-peer computing
P2PR-Tree: an R-tree-based spatial index for peer-to-peer environments
EDBT'04 Proceedings of the 2004 international conference on Current Trends in Database Technology
Similarity grid for searching in metric spaces
DELOS'04 Proceedings of the 6th Thematic conference on Peer-to-Peer, Grid, and Service-Orientation in Digital Library Architectures
Distance browsing in distributed multimedia databases
Future Generation Computer Systems
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Searching for non-text data (e.g., images) is mostly done by means of metadata annotations or by extracting the text close to the data. However, supporting real content-based audio-visual search, based on similarity search on features, is significantly more expensive than searching for text. Moreover, the search exhibits linear scalability with respect to the data set size. In this paper, we present a Distributed Incremental Nearest Neighbor algorithm (DINN) for finding nearest neighbor in an incremental fashion over data distributed between nodes which are able to perform a local Incremental Nearest Neighbor (local-INN). We prove that our algorithm is optimal with respect to both number of involved nodes and number of local-INN invocations. An implementation of our DINN algorithm, on a real P2P system called MCAN, was used for conducting an extensive experimental evaluation on a real-life dataset.