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@inproceedings{593300, author = {Popelínský, Lubomír and Blaťák, Jan}, address = {Porto}, booktitle = {Proceedings of ECML/PKDD Workshop on Mining Spatio-Temporal Data (MSTD),}, keywords = {data mining; spatiotemporal data}, language = {eng}, location = {Porto}, pages = {31-40}, publisher = {UP}, title = {Toward mining of spatiotemporal maximal frequent patterns}, year = {2005} }
TY - JOUR ID - 593300 AU - Popelínský, Lubomír - Blaťák, Jan PY - 2005 TI - Toward mining of spatiotemporal maximal frequent patterns PB - UP CY - Porto KW - data mining KW - spatiotemporal data N2 - We show that propositional spatiotemporal logic PSTL is a powerful tool for mining in various spatiotemporal data including environmental and medical data, keystroke dynamics data or text. We introduce a refinement operator for a fragment of $PSTL$, $ST_0$ and %, and present frequent patterns mined with RAP. describe the ILP system GRAPE for mining first-order frequent patterns in spatiotemporal data. We also show that in the classification task %the use of this refinement operator can %decrease computational cost and that the use of frequent patterns as new features result in an accuracy increase. ER -
POPELÍNSKÝ, Lubomír a Jan BLAŤÁK. Toward mining of spatiotemporal maximal frequent patterns. In \textit{Proceedings of ECML/PKDD Workshop on Mining Spatio-Temporal Data (MSTD),}. Porto: UP, 2005, s.~31-40.
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