%0 Book Section %1 zighed2012topological %A Zighed, DjamelAbdelkader %A Abdesselam, Rafik %A Hadgu, Asmelash %B Advances in Knowledge Discovery and Data Mining %D 2012 %E Tan, Pang-Ning %E Chawla, Sanjay %E Ho, ChinKuan %E Bailey, James %I Springer Berlin Heidelberg %K comparison measures myown proxmity topological %P 379-391 %R 10.1007/978-3-642-30217-6_32 %T Topological Comparisons of Proximity Measures %U http://dx.doi.org/10.1007/978-3-642-30217-6_32 %V 7301 %X In many fields of application, the choice of proximity measure directly affects the results of data mining methods, whatever the task might be: clustering, comparing or structuring of a set of objects. Generally, in such fields of application, the user is obliged to choose one proximity measure from many possible alternatives. According to the notion of equivalence, such as the one based on pre-ordering, certain proximity measures are more or less equivalent, which means that they should produce almost the same results. This information on equivalence might be helpful for choosing one such measure. However, the complexity %@ 978-3-642-30216-9

@incollection{zighed2012topological, abstract = {In many fields of application, the choice of proximity measure directly affects the results of data mining methods, whatever the task might be: clustering, comparing or structuring of a set of objects. Generally, in such fields of application, the user is obliged to choose one proximity measure from many possible alternatives. According to the notion of equivalence, such as the one based on pre-ordering, certain proximity measures are more or less equivalent, which means that they should produce almost the same results. This information on equivalence might be helpful for choosing one such measure. However, the complexity }, added-at = {2013-02-19T16:13:16.000+0100}, author = {Zighed, DjamelAbdelkader and Abdesselam, Rafik and Hadgu, Asmelash}, biburl = {https://www.bibsonomy.org/bibtex/22a849aa5e1d417eb4d64096d9142893d/asmelash}, booktitle = {Advances in Knowledge Discovery and Data Mining}, description = {Topological Comparisons of Proximity Measures - Springer}, doi = {10.1007/978-3-642-30217-6_32}, editor = {Tan, Pang-Ning and Chawla, Sanjay and Ho, ChinKuan and Bailey, James}, interhash = {b44b66c319cc98c2a95136683fb87f3e}, intrahash = {2a849aa5e1d417eb4d64096d9142893d}, isbn = {978-3-642-30216-9}, keywords = {comparison measures myown proxmity topological}, pages = {379-391}, publisher = {Springer Berlin Heidelberg}, series = {Lecture Notes in Computer Science}, timestamp = {2017-02-08T17:28:43.000+0100}, title = {Topological Comparisons of Proximity Measures}, url = {http://dx.doi.org/10.1007/978-3-642-30217-6_32}, volume = 7301, year = 2012 }