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Efficient Peer-to-Peer Semantic . . . (2006)
| Content Provider | CiteSeerX |
|---|---|
| Author | Linari, Alessandro Weikum, Gerhard |
| Abstract | In this paper we address the query routing problem in peerto-peer (P2P) information retrieval. Our system builds up on the idea of a Semantic Overlay Network (SON), in which each peer becomes neighbor of a small number of peers, chosen among those that are most similar to it. Peers in the network are represented by a statistical Language Model derived from their local data collections but, instead of using the non-metric Kullback-Leibler divergence to compute the similarity between them, we use a symmetrized and “metricized ” related measure, the square root of the Jensen-Shannon divergence, which let us map the problem to a metric search problem. The search strategy exploits the triangular inequality to efficiently prune the search space and relies on a priority queue to visit the most promising peers first. To keep communications costs low and to perform an efficient comparison between Language Models, we devise a compression technique that builds on Bloom-filters and histograms and we provide error bounds for the approximation and a cost analysis for the algorithms used to build and maintain the SON. |
| File Format | |
| Publisher Date | 2006-01-01 |
| Access Restriction | Open |
| Subject Keyword | Efficient Peer-to-peer Semantic Information Retrieval Communication Cost Promising Peer Cost Analysis Statistical Language Model Related Measure Search Space Language Model Triangular Inequality Semantic Overlay Network Local Data Collection Metric Search Problem Jensen-shannon Divergence Non-metric Kullback-leibler Divergence Priority Queue Efficient Comparison Square Root Error Bound Search Strategy Compression Technique |
| Content Type | Text |
| Resource Type | Article |
