The M-tree is an index structure that can be used for the efficient resolution of similarity queries on complex objects to be compared using an arbitrary metric, i.e. a distance function d that satisfies the positivity, symmetry, and triangle inequality p
K. Lang. Proceedings of the 12th International Conference on Machine Learning, стр. 331--339. Morgan Kaufmann publishers Inc.: San Mateo, CA, USA, (1995)
K. Lang. Proceedings of the 12th International Conference on Machine Learning, стр. 331--339. Morgan Kaufmann publishers Inc.: San Mateo, CA, USA, (1995)
R. Cole, P. Eklund, и B. Groh. International Symposium on Knowledge Retrieval, Use, and Storage for Efficiency, KRUSE-97, стр. 151-164. (1997)Later revised and published completely in Cole's Computational Intelligence paper.
A. Hotho, R. Jäschke, C. Schmitz, и G. Stumme. The Semantic Web: Research and Applications, том 4011 из LNAI, стр. 411-426. Heidelberg, Springer, (2006)
A. Hotho, R. Jäschke, C. Schmitz, и G. Stumme. The Semantic Web: Research and Applications, том 4011 из LNAI, стр. 411-426. Heidelberg, Springer, (2006)
M. Strohmaier, M. Lux, M. Granitzer, P. Scheir, S. Liaskos, и E. Yu. We Know'07 International Workshop on Collaborative Knowledge Management for Web Information Systems, in conjunction with WISE'07, Nancy, France, (2007)