%0 Book Section %1 Rendon2008 %A Rendón, Eréndira %A Sánchez, J %A Garcia, Rene %A Abundez, Itzel %A Gutierrez, Citlalih %A Gasca, Eduardo %B Adv. Artif. Intell. – IBERAMIA 2008 %D 2008 %K clustering_db_entityguides_phd_summary phd %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 = {2013-12-17T09:48:27.000+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/2822239eeaa2020e6a134992d453aea7d/jullybobble}, booktitle = {Adv. Artif. Intell. – IBERAMIA 2008}, doi = {http://dx.doi.org/10.1007/978-3-540-88309-8\_15}, interhash = {2da84b813f8ae3d0ec312aab4375f417}, intrahash = {822239eeaa2020e6a134992d453aea7d}, keywords = {clustering_db_entityguides_phd_summary phd}, pages = {143--152}, timestamp = {2014-07-27T15:43:19.000+0200}, title = {{Data Reduction Method for Categorical Data Clustering}}, url = {http://dx.doi.org/10.1007/978-3-540-88309-8\_15}, year = 2008 }