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A probabilistic approach to metasearching with adaptive probing
Proceedings. 20th International Conference on Data Engineering
An ever increasing amount of valuable information is stored in Web databases, "hidden" behind search interfaces. To save the user's effort in manually exploring each database, metasearchers automatically select the most relevant databases to a user's query [2, 5, 16, 21, 27, 18] . In this paper, we focus on the first of the two technical challenges of metasearching, namely database selection. Past research uses a pre-collected summary of each database to estimate its "relevancy" to the query,doi:10.1109/icde.2004.1320026 dblp:conf/icde/LiuLCC04 fatcat:etxtq5sghjcmpohqk4vecwarqm