Diamond-Tree: An Index Structure for High-Dimensionality Approximate Searching

dc.contributor.authorFaloutsos, Christosen_US
dc.contributor.authorJagadish, H.V.en_US
dc.contributor.departmentISRen_US
dc.date.accessioned2007-05-23T09:51:35Z
dc.date.available2007-05-23T09:51:35Z
dc.date.issued1992en_US
dc.description.abstractA selection query applied to a database often has the selection predicate imperfectly specified. We present a technique, called the Diamond-tree, for indexing fields to perform similarity-based retrieval, given some applicable measures of approximation. Typically, the number of features (or dimensions of similarity) is large, so that the search space has a high-dimensionality, and most traditional methods perform poorly. As a test case, we show how the Diamond-tree technique can be used to perform retrievals based on incorrectly or approximately specified values for string fields. Experimental results show that our method can respond to approximately match queries by examining a small portion (1% - 5%) of the database.en_US
dc.format.extent951397 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/1903/5278
dc.language.isoen_USen_US
dc.relation.ispartofseriesISR; TR 1992-97en_US
dc.subjectdatabasesen_US
dc.subjectdata structuresen_US
dc.subjectChemical Process Systemsen_US
dc.subjectapproximate searchingen_US
dc.subjectmanufacturing systemsen_US
dc.titleDiamond-Tree: An Index Structure for High-Dimensionality Approximate Searchingen_US
dc.typeTechnical Reporten_US

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