The effect of adding relevance information in a relevance feedback environment
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Query expansion using local and global document analysis
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Effective retrieval with distributed collections
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Methods for information server selection
ACM Transactions on Information Systems (TOIS)
Comparing the performance of database selection algorithms
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
GlOSS: text-source discovery over the Internet
ACM Transactions on Database Systems (TODS)
Server selection on the World Wide Web
DL '00 Proceedings of the fifth ACM conference on Digital libraries
The impact of database selection on distributed searching
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in 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
Query-based sampling of text databases
ACM Transactions on Information Systems (TOIS)
ECDL '97 Proceedings of the First European Conference on Research and Advanced Technology for Digital Libraries
Server Ranking for Distributed Text Retrieval Systems on the Internet
Proceedings of the Fifth International Conference on Database Systems for Advanced Applications (DASFAA)
Pruning long documents for distributed information retrieval
Proceedings of the eleventh international conference on Information and knowledge management
SDQE: towards automatic semantic query optimization in P2P systems
Information Processing and Management: an International Journal - Special issue: Formal methods for information retrieval
Does pseudo-relevance feedback improve distributed information retrieval systems?
Information Processing and Management: an International Journal
A simple solution for improving the effectiveness of traditional information retrieval systems
SEPADS'05 Proceedings of the 4th WSEAS International Conference on Software Engineering, Parallel & Distributed Systems
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
Robust result merging using sample-based score estimates
ACM Transactions on Information Systems (TOIS)
Effective query expansion for federated search
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
SDQE: towards automatic semantic query optimization in P2P systems
Information Processing and Management: an International Journal - Special issue: Formal methods for information retrieval
Reverted indexing for feedback and expansion
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Foundations and Trends in Information Retrieval
Aggregating evidence from hospital departments to improve medical records search
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
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Query expansion has been shown effective for both single database retrieval and for distributed information retrieval where complete collection information is available. One might expect that query expansion would then work for distributed information retrieval when complete collection information is not available. However, this does not appear to be the case. When using local context analysis for query expansion in distributed retrieval with partial information, the most significant reason query expansion does not work is that merging scores of documents retrieved by expanded queries is very difficult. However, we have found that using sampled information for query expansion can give boosts in a single database environment, and that when more information is available, query expansion can work in distributed environments. We also show that most of the benefit of query expansion in distributed retrieval comes from finding good documents, and not from selecting good databases.