Searching distributed collections with inference networks
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
Learning collection fusion strategies
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
Experiences with selecting search engines using metasearch
ACM Transactions on Information Systems (TOIS)
Analyses of multiple evidence combination
Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval
Efficient and effective metasearch for a large number of text databases
Proceedings of the eighth international conference on Information and knowledge management
Server selection on the World Wide Web
DL '00 Proceedings of the fifth ACM conference on Digital libraries
Database merging strategy based on logistic regression
Information Processing and Management: an International Journal
Building efficient and effective metasearch engines
ACM Computing Surveys (CSUR)
Expert agreement and content based reranking in a meta search environment using Mearf
Proceedings of the 11th international conference on World Wide Web
Using sampled data and regression to merge search engine results
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Fusion Via a Linear Combination of Scores
Information Retrieval
Context and Page Analysis for Improved Web Search
IEEE Internet Computing
Improving the evaluation of web search systems
ECIR'03 Proceedings of the 25th European conference on IR research
Result merging methods in distributed information retrieval with overlapping databases
Information Retrieval
Probability-based fusion of information retrieval result sets
Artificial Intelligence Review
Information Processing and Management: an International Journal
Foundations and Trends in Information Retrieval
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In distributed information retrieval systems, document overlaps occur frequently across results from different databases. This is especially the case for meta-search engines which merge results from several general-purpose web search engines. This paper addresses the problem of merging results which contain overlaps in order to achieve better performance. Several algorithms for merging results are proposed, which take advantage of the use of duplicate documents in two ways: one correlates scores from different results; the other regards duplicates as increasing evidence of being relevant to the given query. A variety of experiments have demonstrated that these methods are effective.