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My similarity search seminar topic are M-trees. I would like to give some examples about where they are practically applied, but I can't find anything googling.

Does someone know if M-trees are still used and what for? I am interested in answers regarding both practice and applied research.

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M-trees appear in this survey of image retrieval techniques (emphasis added):

In Berretti et al. [2000], curves are represented by a set of segments, or tokens, whose feature representations (curvature and orientation) are arranged into a metric tree [Ciaccia et al. 1997] for efficient shape matching and shape-based image retrieval.

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Digital libraries, databases and the WWW contain huge amounts of information. Any multimedia is first characterized by relevant features; think of shapes, textures, patterns, colors, loudness and harmonicity for sounds, and so on. There's applications everywhere, for example in image processing, geography systems, medical applications, and biomedicine. See the introductions in [1] and [2].


[1] Ciaccia, P., Patella, M., Rabitti, F., & Zezula, P. (1997, June). Indexing Metric Spaces with M-Tree. In SEBD (Vol. 97, pp. 67-86).

[2] Zhou, X., Wang, G., Yu, J. X., & Yu, G. (2003, January). M+-tree: a new dynamical multidimensional index for metric spaces. In Proceedings of the 14th Australasian database conference-Volume 17 (pp. 161-168). Australian Computer Society, Inc.

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