Improving the effectiveness of information retrieval with local context analysis
ACM Transactions on Information Systems (TOIS)
Chord: A scalable peer-to-peer lookup service for internet applications
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
Peer-to-Peer Keyword Search Using Keyword Relationship
CCGRID '03 Proceedings of the 3st International Symposium on Cluster Computing and the Grid
Peer-to-peer information retrieval using self-organizing semantic overlay networks
Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
Information Retrieval: Algorithms and Heuristics (The Kluwer International Series on Information Retrieval)
Progressive Distributed Top-k Retrieval in Peer-to-Peer Networks
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Speeding up search in peer-to-peer networks with a multi-way tree structure
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
User modeling for full-text federated search in peer-to-peer networks
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Web text retrieval with a P2P query-driven index
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Online query relaxation via Bayesian causal structures discovery
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 2
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Peer-to-peer file-sharing systems suffer from the over-specification of query results due to the fact that query processing is conjunctive and the descriptions of shared files are sparse. Ultimately, longer queries, which should yield more accurate results, do the opposite. To alleviate this problem, we consider alternative means of query processing. That is, results are sent from the server to the client only if they are deemed relevant based on cosine similarity. Based on our results, these alternatives can increase query accuracy by 40% at virtually no cost.