Searching distributed collections with inference networks
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
Analyses of multiple evidence combination
Proceedings of the 20th 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)
Real life, real users, and real needs: a study and analysis of user queries on the web
Information Processing and Management: an International Journal
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
Query-based sampling of text databases
ACM Transactions on Information Systems (TOIS)
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
A language modeling framework for resource selection and results merging
Proceedings of the eleventh international conference on Information and knowledge management
Proceedings of the 27th 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)
Combining document representations for known-item search
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Evaluating different methods of estimating retrieval quality for resource selection
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Relevant document distribution estimation method for resource selection
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
STARTS: Stanford Protocol Proposal for Internet Retrieval and Search
STARTS: Stanford Protocol Proposal for Internet Retrieval and Search
Comparing the performance of collection selection algorithms
ACM Transactions on Information Systems (TOIS)
A semisupervised learning method to merge search engine results
ACM Transactions on Information Systems (TOIS)
Engineering a multi-purpose test collection for web retrieval experiments
Information Processing and Management: an International Journal
Unified utility maximization framework for resource selection
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Server selection methods in hybrid portal search
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Modeling search engine effectiveness for federated search
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
The FedLemur project: Federated search in the real world
Journal of the American Society for Information Science and Technology
Capturing collection size for distributed non-cooperative retrieval
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Voting for candidates: adapting data fusion techniques for an expert search task
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Evaluating sampling methods for uncooperative collections
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Central-rank-based collection selection in uncooperative distributed information retrieval
ECIR'07 Proceedings of the 29th European conference on IR research
Adaptive query-based sampling of distributed collections
SPIRE'06 Proceedings of the 13th international conference on String Processing and Information Retrieval
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Source selection deals with the problem of selecting the most appropriate information sources from the set of, usually non-intersecting, available document collections. On the other hand, data fusion techniques (also known as metasearch techniques) deal with the problem of aggregating the results from multiple, usually completely or partly intersecting, document sources in order to provide a wider coverage and a more effective retrieval result. In this paper we study some simple adaptations to traditional data fusion algorithms for the task of source selection in uncooperative distributed information retrieval environments. The experiments demonstrate that the performance of data fusion techniques at source selection tasks is comparable with that of state-of-the-art source selection algorithms and they are often able to surpass them.