Association Mining in Large Databases: A Re-examination of Its Measures

@incollection{citeulike:2801923, abstract = {In the literature of data mining and statistics, numerous interestingness measures have been proposed to disclose succinct object relationships of association patterns. However, it is still not clear when a measure is truly effective in large data sets. Recent studies have identified a critical property, null-(transaction) invariance, for measuring event associations in large data sets, but many existing measures do not have this property. We thus re-examine the null-invariant measures and find interestingly that they can be expressed as a generalized mathematical mean, and there exists a total ordering of them. This ordering provides insights into the underlying philosophy of the measures and helps us understand and select the proper measure for different applications.}, author = {Wu, Tianyi and Chen, Yuguo and Han, Jiawei }, citeulike-article-id = {2801923}, doi = {http://dx.doi.org/10.1007/978-3-540-74976-9\_66}, journal = {Knowledge Discovery in Databases: PKDD 2007}, keywords = {association, measure, rules}, pages = {621--628}, posted-at = {2008-05-15 15:58:04}, priority = {2}, title = {Association Mining in Large Databases: A Re-examination of Its Measures}, url = {http://dx.doi.org/10.1007/978-3-540-74976-9\_66}, year = {2007} }

TY - CHAP ID - citeulike:2801923 L3 - citeulike-article-id:2801923 TI - Association Mining in Large Databases: A Re-examination of Its Measures JF - Knowledge Discovery in Databases: PKDD 2007 SP - 621 EP - 628 N2 - In the literature of data mining and statistics, numerous interestingness measures have been proposed to disclose succinct object relationships of association patterns. However, it is still not clear when a measure is truly effective in large data sets. Recent studies have identified a critical property, null-(transaction) invariance, for measuring event associations in large data sets, but many existing measures do not have this property. We thus re-examine the null-invariant measures and find interestingly that they can be expressed as a generalized mathematical mean, and there exists a total ordering of them. This ordering provides insights into the underlying philosophy of the measures and helps us understand and select the proper measure for different applications. KW - association KW - measure KW - rules AU - Wu, Tianyi AU - Chen, Yuguo AU - Han, Jiawei PY - 2007/// UR - http://dx.doi.org/10.1007/978-3-540-74976-9_66 ER -