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ABSTRACT
The problem of searching the set of keys in a file to find a key which is closest to a given query key is discussed. After “closest,” in terms of a metric on the the key space, is suitably defined, three file structures are presented together with their corresponding search algorithms, which are intended to reduce the number of comparisons required to achieve the desired result. These methods are derived using certain inequalities satisfied by metrics and by graph-theoretic concepts. Some empirical results are presented which compare the efficiency of the methods.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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CITED BY 47
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Caetano Traina, Jr. , Agma Traina , Roberto Santos Filho , Christos Faloutsos, How to improve the pruning ability of dynamic metric access methods, Proceedings of the eleventh international conference on Information and knowledge management, November 04-09, 2002, McLean, Virginia, USA
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Caetano Traina, Jr. , Roberto F. Filho , Agma J. Traina , Marcos R. Vieira , Christos Faloutsos, The Omni-family of all-purpose access methods: a simple and effective way to make similarity search more efficient, The VLDB Journal — The International Journal on Very Large Data Bases, v.16 n.4, p.483-505, October 2007
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Dragomir Yankov , Eamonn Keogh , Jose Medina , Bill Chiu , Victor Zordan, Detecting time series motifs under uniform scaling, Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining, August 12-15, 2007, San Jose, California, USA
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