CloSpan: Mining Closed Sequential Patterns in Large Datasets Export

@inproceedings{citeulike:6012287, abstract = {Previous sequential pattern mining algorithms mine the full set of frequent subsequences satisfying a rain\_sup threshold in a sequence database. However, since a frequent long sequence contains a combinatorial number of frequent subsequences, such mining will generate an explosive number of frequent subsequences for long patterns, which is prohibitively expensive in both time and space.}, author = {Yan, Xifeng and Han, Jiawei and Afshar, Ramin}, booktitle = {In SDM}, citeulike-article-id = {6012287}, citeulike-linkout-0 = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.12.3538}, keywords = {mining, pattern, sequential}, pages = {166--177}, posted-at = {2009-10-26 20:01:01}, priority = {2}, title = {CloSpan: Mining Closed Sequential Patterns in Large Datasets}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.12.3538}, year = {2003} }

TY - CONF ID - citeulike:6012287 L3 - citeulike-article-id:6012287 N2 - Previous sequential pattern mining algorithms mine the full set of frequent subsequences satisfying a rain_sup threshold in a sequence database. However, since a frequent long sequence contains a combinatorial number of frequent subsequences, such mining will generate an explosive number of frequent subsequences for long patterns, which is prohibitively expensive in both time and space. EP - 177 TI - CloSpan: Mining Closed Sequential Patterns in Large Datasets T2 - In SDM SP - 166 KW - mining KW - pattern KW - sequential AU - Yan, Xifeng AU - Han, Jiawei AU - Afshar, Ramin PY - 2003/// UR - http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.12.3538 ER -