M-tree: An Efficient Access Method for Similarity Search in Metric Spaces

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M-tree: An Efficient Access Method for Similarity Search in Metric Spaces (1997)

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by Paolo Ciaccia , Marco Patella , Pavel Zezula

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650 - 38 self

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@INPROCEEDINGS{Ciaccia97m-tree:an,
    author = {Paolo Ciaccia and Marco Patella and Pavel Zezula},
    title = {M-tree: An Efficient Access Method for Similarity Search in Metric Spaces},
    booktitle = {},
    year = {1997},
    pages = {426--435}
}

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Abstract

A new access meth d, called M-tree, is proposed to organize and search large data sets from a generic "metric space", i.e. whE4 object proximity is only defined by a distance function satisfyingth positivity, symmetry, and triangle inequality postulates. We detail algorith[ for insertion of objects and split management, whF h keep th M-tree always balanced - severalheralvFV split alternatives are considered and experimentally evaluated. Algorithd for similarity (range and k-nearest neigh bors) queries are also described. Results from extensive experimentationwith a prototype system are reported, considering as th performance criteria th number of page I/O's and th number of distance computations. Th results demonstratethm th Mtree indeed extendsth domain of applicability beyond th traditional vector spaces, performs reasonably well inhE[94Kv#E44V[vh data spaces, and scales well in case of growing files. 1

Keyphrases

efficient access method similarity search metric space distance computation distance function satisfyingth positivity triangle inequality postulate th result large data set whe4 object proximity e44v vh data space th performance criterion generic metric space th number th traditional vector space severalheralvfv split alternative k-nearest neigh bors prototype system split management extensive experimentationwith new access meth th mtree

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