Publication details
Adaptive Approximate Similarity Searching through Metric Social Networks
| Basic information | |
|---|---|
| Original title: | Adaptive Approximate Similarity Searching through Metric Social Networks |
| Authors: | Jan Sedmidubský, Stanislav Bartoň, Vlastislav Dohnal, Pavel Zezula |
| Further information | |
|---|---|
| Citation: | SEDMIDUBSKÝ, Jan  - BARTOŇ, Stanislav - DOHNAL, Vlastislav - ZEZULA, Pavel. Adaptive Approximate Similarity Searching through Metric Social Networks. Brno : Faculty of Informatics, Masaryk University, 2007. Technical report FIMU-RS-2007-06. |
| Original language: | English |
| Field: | Informatika |
| WWW: |  PDF file |
| Type: | R&D Presentation |
| Keywords: | metric social network; similarity searching |
Exploiting the concepts of social networking represents a novel approach to the approximate similarity query processing. We present an unstructured and dynamic P2P environment in which a metric social network is built. Social communities of peers giving similar results to specific queries are established and such ties are exploited for answering future queries. Based on the universal law of generalization, a new query forwarding algorithm is introduced and evaluated. The same principle is used to manage query histories of individual peers with the possibility to tune the tradeoff between the extent of the history and the level of the query-answer approximation. All proposed algorithms are tested on real data and medium-sized P2P networks consisting of tens of computers.
Related projects:
- Intelligent Models, Algorithms, Methods and Tools for the Semantic Web (realization)
- Distributed Index Structures for Similarity Searching
