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Surrogate ranking for very expensive similarity queries
2010
2010 IEEE 26th International Conference on Data Engineering (ICDE 2010)
1 We consider the problem of similarity search in applications where the cost of computing the similarity between two records is very expensive, and the similarity measure is not a metric. In such applications, comparing even a tiny fraction of the database records to a single query record can be orders of magnitude slower than reading the entire database from disk, and indexing is often not possible. We develop a general-purpose, statistical framework for answering top-k queries in such
doi:10.1109/icde.2010.5447888
dblp:conf/icde/XuJWJK10
fatcat:eul6wx4fh5gf3ff3eqh7kzzzqq