Publication details

Similarity Search in P2P Networks

Authors

BATKO Michal

Year of publication 2004
Type Article in Proceedings
Conference Proceedings of the PhD Wokshops of the EDBT and ICDE Conferences
MU Faculty or unit

Institute of Computer Science

Citation
Field Computer hardware and software
Keywords P2P; distributed data; scalable structures; similarity search; metric space
Description we address the problem of scalable distributed similarity searching. Our work is based on single-site metric space indexing algorithms. They provide efficient way to perform range and nearest neighbor queries on arbitrary data in general metric spaces. The metric spaces are excellent abstraction that allows comparison of very complex objects (such as audio files, DNA sequences, texts). We have exploited the SDDS (Scalable and Distributed Data Structures) paradigms and P2P (Peer to Peer) systems to form a metric space similarity searching structure in distributed environment. Our proposed method is fully scalable without any centralized part and it allows performing similarity queries on stored data.
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