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Abstract: A new access method, called M-tree, is proposed to organize and search large data sets from a generic "metric space", i.e. where object proximity is only defined by a distance function satisfying the positivity, symmetry, and triangle inequality postulates. We detail algorithms for insertion of objects and split management, which keep the M-tree always balanced - several heuristic split alternatives are considered and experimentally evaluated. Algorithms for similarity (range and k-nearest... (Update)
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BibTeX entry: (Update)
P. Ciaccia, M. Patella, and P. Zezula, "M-tree: An efficient access method for similarity search in metric spaces," Proceedings of the 23rd VLDB , August 1997. http://citeseer.ist.psu.edu/ciaccia97mtree.html More
@inproceedings{ ciaccia97mtree,
author = "Paolo Ciaccia and Marco Patella and Pavel Zezula",
title = "M-tree: An Efficient Access Method for Similarity Search in Metric Spaces",
booktitle = "The {VLDB} Journal",
pages = "426-435",
year = "1997",
url = "citeseer.ist.psu.edu/ciaccia97mtree.html" }
Citations (may not include all citations):516 tree: An efficient and robust access method for points and r.. (context) - Beckmann, Kriegel et al. - 1990
205 Efficient similarity search in sequence databases - Agrawal, Faloutsos et al. - 1993
204 tree: An index structure for highdimensional data (context) - Berchtold, Keim et al. - 1996
The graph only includes citing articles where the year of publication is known.
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