PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Dohnal V., Gennaro C., Zezula P. Similarity Join in Metric Spaces Using eD-Index. In: Database and Expert Systems Applications (Prague, Czech Republic, 1-5 September 2003). Proceedings, pp. 484 - 493. Marík, Vladimír and Retschitzegger, Werner and Stepánková , Olga (eds.). (Lecture Notes in Computer Science, vol. 2736). Springer Verlag, 2003.
 
 
Abstract
(English)
Similarity join in distance spaces constrained by the metric postulates is the necessary complement of more famous similarity range and the nearest neighbor search primitives. However, the quadratic computational complexity of similarity joins prevents from applications on large data collections. We present the eD-Index, an extension of D-index, and we study an application of the eDIndex to implement two algorithms for similarity self joins, i.e. the range query join and the overloading join. Though also these approaches are not able to eliminate the intrinsic quadratic complexity of similarity joins, significant performance improvements are confirmed by experiments.
Subject Metric spaces
similarity join
index structures
performance
H.3.4 Systems and Software. Performance evaluation (efficiency and effectiveness)


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