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@inproceedings{486137,
author = {Dohnal, Vlastislav and Gennaro, Claudio and Savino, Pasquale and Zezula, Pavel},
address = {Berlin},
booktitle = {Proceedings of the European Conference on Information Retrieval Research},
edition = {LNCS 2633},
keywords = {similarity join; index structures; performance; text management},
howpublished = {tištěná verze "print"},
language = {eng},
location = {Berlin},
isbn = {3-540-01274-5},
pages = {452-467},
publisher = {Springer-Verlag},
title = {Similarity Join in Metric Spaces},
year = {2003}
}
TY - JOUR
ID - 486137
AU - Dohnal, Vlastislav - Gennaro, Claudio - Savino, Pasquale - Zezula, Pavel
PY - 2003
TI - Similarity Join in Metric Spaces
PB - Springer-Verlag
CY - Berlin
SN - 3540012745
KW - similarity join
KW - index structures
KW - performance
KW - text management
N2 - Similarity join in distance spaces constrained by the metric postulates is the necessary complement of more famous similarity range and the nearest neighbors search primitives. However, the quadratic computational complexity of similarity joins prevents from applications on large data collections. We first study the underlying principles of such joins and suggest three categories of implementation strategies based on filtering, partitioning, or similarity range searching. Then we study an application of the D-index to implement the most promising alternative of range searching. Though also this approach is not able to eliminate the intrinsic quadratic complexity of similarity joins, significant performance improvements are confirmed by experiments.
ER -
DOHNAL, Vlastislav, Claudio GENNARO, Pasquale SAVINO a Pavel ZEZULA. Similarity Join in Metric Spaces. In \textit{Proceedings of the European Conference on Information Retrieval Research}. LNCS 2633. Berlin: Springer-Verlag. s.~452-467. ISBN~3-540-01274-5. 2003.
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