The effectiveness of GIOSS for the text database discovery problem
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Determining information retrieval and filtering performance without experimentation
Information Processing and Management: an International Journal
Searching distributed collections with inference networks
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
Data structures for efficient broker implementation
ACM Transactions on Information Systems (TOIS)
Nonparametric methods for quantitative analysis (3rd ed.)
Nonparametric methods for quantitative analysis (3rd ed.)
Effective retrieval with distributed collections
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Evaluating database selection techniques: a testbed and experiment
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
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)
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
Precision and Recall of GlOSS Estimators for Database Discovery
PDIS '94 Proceedings of the Third International Conference on Parallel and Distributed Information Systems
Determining Text Databases to Search in the Internet
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Generalizing GlOSS to Vector-Space Databases and Broker Hierarchies
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Server Ranking for Distributed Text Retrieval Systems on the Internet
Proceedings of the Fifth International Conference on Database Systems for Advanced Applications (DASFAA)
Effective and Efficient Automatic Database Selection
Effective and Efficient Automatic Database Selection
Exploiting a controlled vocabulary to improve collection selection and retrieval effectiveness
Proceedings of the tenth international conference on Information and knowledge management
Exploiting Manual Indexing to Improve Collection Selection and Retrieval Effectiveness
Information Retrieval
Comparing the performance of collection selection algorithms
ACM Transactions on Information Systems (TOIS)
A new perspective on collection selection
ECDL'10 Proceedings of the 14th European conference on Research and advanced technology for digital libraries
Foundations and Trends in Information Retrieval
Assessing and predicting vertical intent for web queries
ECIR'12 Proceedings of the 34th European conference on Advances in Information Retrieval
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The increasing availability of online databases and other information resources in digital libraries and on the World Wide Web has created the need for efficient and effective algorithms for selecting databases to search. A number of techniques have been proposed for query routing or database selection. We have developed a methodology and metrics that can be used to directly compare competing techniques. They can also be used to isolate factors that influence the performance of these techniques so that we can better understand performance issues. In this paper we describe the methodology we have used to examine the performance of database selection algorithms such as gGlOSS and CORI. In addition we develop the theory behind a “random” database selection algorithm and show how it can be used to help analyze the behavior of realistic database selection algorithms.