Searching distributed collections with inference networks
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
A language modeling approach to information retrieval
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
A probabilistic solution to the selection and fusion problem in distributed information retrieval
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Cluster-based language models for distributed retrieval
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
A decision-theoretic approach to database selection in networked IR
ACM Transactions on Information Systems (TOIS)
GlOSS: text-source discovery over the Internet
ACM Transactions on Database Systems (TODS)
A language modeling approach to information retrieval
A language modeling approach to information retrieval
Collection selection and results merging with topically organized U.S. patents and TREC data
Proceedings of the ninth international conference on Information and knowledge management
Optimal aggregation algorithms for middleware
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
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
Model-based feedback in the language modeling approach to information retrieval
Proceedings of the tenth international conference on Information and knowledge management
A language modeling framework for resource selection and results merging
Proceedings of the eleventh international conference on Information and knowledge management
Server Ranking for Distributed Text Retrieval Systems on the Internet
Proceedings of the Fifth International Conference on Database Systems for Advanced Applications (DASFAA)
PlanetP: Using Gossiping to Build Content Addressable Peer-to-Peer Information Sharing Communities
HPDC '03 Proceedings of the 12th IEEE International Symposium on High Performance Distributed Computing
Merging retrieval results in hierarchical peer-to-peer networks
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Progressive Distributed Top-k Retrieval in Peer-to-Peer Networks
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
KLEE: a framework for distributed top-k query algorithms
VLDB '05 Proceedings of the 31st international conference on Very large data bases
p2pDating: Real life inspired semantic overlay networks for Web search
Information Processing and Management: an International Journal
Chora: Expert-Based P2P Web Search
Agents and Peer-to-Peer Computing
Ranking information resources in peer-to-peer text retrieval: an experimental study
Proceedings of the 2008 ACM workshop on Large-Scale distributed systems for information retrieval
LCA-based selection for XML document collections
Proceedings of the 19th international conference on World wide web
Peer-to-Peer Information Retrieval: An Overview
ACM Transactions on Information Systems (TOIS)
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Intelligent Web search engines are extremely popular now. Currently, only commercial centralized search engines like Google can process terabytes of Web data. Alternative search engines fulfilling collaborative Web search on a voluntary basis are usually based on a blooming Peer-to-Peer (P2P) technology. In this paper, we investigate the effectiveness of different database selection and result merging methods in the scope of P2P Web search engine Minerva. We adapt existing measures for database selection and results merging, all directly derived from popular document ranking measures, to address the specific issues of P2P Web search. We propose a general approach to both tasks based on the combination of pseudo-relevance feedback methods. From experiments with TREC Web data, we observe that pseudo-relevance feedback improves quality of distributed information retrieval.