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Dimensionality reduction for similarity searching in dynamic databases
1998
Proceedings of the 1998 ACM SIGMOD international conference on Management of data - SIGMOD '98
Databases are increasingly being used to store multi-media objects such as maps, images, audio and video. Storage and retrieval of these objects is accomplished using multi-dimensional index structures such as R ¢ -trees and SS-trees. As dimensionality increases, query performance in these index structures degrades. This phenomenon, generally referred to as the dimensionality curse, can be circumvented by reducing the dimensionality of the data. Such a reduction is however accompanied by a loss
doi:10.1145/276304.276320
dblp:conf/sigmod/KanthAS98
fatcat:tlgv5xput5c5jgexfy7s5pp44u