Efficient peer-to-peer keyword searching
Patrick Reynolds,Amin Vahdat +1 more
- pp 21-40
TLDR
A distributed search engine based on a distributed hash table is designed and analyzed and the simulation results predict that the search engine can answer an average query in under one second, using under one kilobyte of bandwidth.Abstract:
The recent file storage applications built on top of peer-to-peer distributed hash tables lack search capabilities. We believe that search is an important part of any document publication system. To that end, we have designed and analyzed a distributed search engine based on a distributed hash table. Our simulation results predict that our search engine can answer an average query in under one second, using under one kilobyte of bandwidth.read more
Citations
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Proceedings ArticleDOI
Content-Based Image Retrieval in P2P Networks with Bag-of-Features
TL;DR: A novel online sampling mechanism is designed to create a codebook with low network cost and two static index pruning policies are implemented to limit the document length and the returned term weights.
Dissertation
Resource Location Mechanisms for Complex Networks Based on Random Walks
López Millán,Víctor Manuel +1 more
TL;DR: Tesis Doctoral leida en la Universidad Rey Juan Carlos en 2013 as discussed by the authors, presented by Antonio Fernandez Anta and Luis Lopez Fernandez. Directores de la Tesis:
Query-Driven Indexing in Large-Scale Distributed Systems
TL;DR: In this paper, the authors introduce the concept of query-driven indexing, which is an index construction strategy that uses caching techniques to adapt to the querying patterns expressed by users, and propose several indexing strategies for processing multi-keyword and XPath queries over distributed collections of textual and XML documents respectively.
Journal Article
Content Aggregation on Knowledge Bases Using Graph Clustering
TL;DR: In this paper, a graph clustering technique on knowledge bases for peer-to-peer knowledge management (P2PKM) systems is proposed, which requires up to 58% fewer queries than the baselines to yield full recall.
References
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Journal Article
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Sergey Brin,Lawrence Page +1 more
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Proceedings ArticleDOI
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