%0 Book Section %1 Rendon2008 %A Rendón, Eréndira %A Sánchez, J. %A Garcia, Rene %A Abundez, Itzel %A Gutierrez, Citlalih %A Gasca, Eduardo %D 2008 %J Advances in Artificial Intelligence – IBERAMIA 2008 %K clustering db entityguides phd summary %P 143--152 %R http://dx.doi.org/10.1007/978-3-540-88309-8\_15 %T Data Reduction Method for Categorical Data Clustering %U http://dx.doi.org/10.1007/978-3-540-88309-8\_15 %X Categorical data clustering constitutes an important part of data mining; its relevance has recently drawn attention from several researchers. As a step in data mining, however, clustering encounters the problem of large amount of data to be processed. This article offers a solution for categorical clustering algorithms when working with high volumes of data by means of a method that summarizes the database. This is done using a structure called CM-tree. In order to test our method, the K-Modes and Click clustering algorithms were used with several databases. Experiments demonstrate that the proposed summarization method improves execution time, without losing clustering quality.

@incollection{Rendon2008, abstract = {Categorical data clustering constitutes an important part of data mining; its relevance has recently drawn attention from several researchers. As a step in data mining, however, clustering encounters the problem of large amount of data to be processed. This article offers a solution for categorical clustering algorithms when working with high volumes of data by means of a method that summarizes the database. This is done using a structure called CM-tree. In order to test our method, the K-Modes and Click clustering algorithms were used with several databases. Experiments demonstrate that the proposed summarization method improves execution time, without losing clustering quality.}, added-at = {2009-03-12T15:42:50.000+0100}, author = {Rend\'{o}n, Er\'{e}ndira and S\'{a}nchez, J. and Garcia, Rene and Abundez, Itzel and Gutierrez, Citlalih and Gasca, Eduardo}, biburl = {https://www.bibsonomy.org/bibtex/20854a9e4e39403932e07076e489ec09a/lillejul}, citeulike-article-id = {3987830}, doi = {http://dx.doi.org/10.1007/978-3-540-88309-8\_15}, interhash = {2da84b813f8ae3d0ec312aab4375f417}, intrahash = {0854a9e4e39403932e07076e489ec09a}, journal = {Advances in Artificial Intelligence – IBERAMIA 2008}, keywords = {clustering db entityguides phd summary}, pages = {143--152}, posted-at = {2009-01-31 09:34:44}, priority = {3}, timestamp = {2009-03-12T15:42:50.000+0100}, title = {Data Reduction Method for Categorical Data Clustering}, url = {http://dx.doi.org/10.1007/978-3-540-88309-8\_15}, year = 2008 }