Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Dee Jay Randall"'
Publikováno v:
Journal of Applied Logic. 4:192-214
We describe a method for spatio-temporal data mining based on GenSpace graphs. Using familiar calendar and geographical concepts, such as workdays, weeks, climatic regions, and countries, spatio-temporal data can be aggregated into summaries in many
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5e23c801dd67e785668785f3ee5f67a9
https://doi.org/10.1016/j.jal.2005.06.005
https://doi.org/10.1016/j.jal.2005.06.005
Publikováno v:
International Journal of Pattern Recognition and Artificial Intelligence. 13:195-217
This paper addresses the problem of using domain generalization graphs to generalize temporal data extracted from relational databases. A domain generalization graph associated with an attribute defines a partial order which represents a set of gener
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::07b5e98894181d6c37d2b6502b127f5c
https://doi.org/10.1142/s0218001499000124
https://doi.org/10.1142/s0218001499000124
Publikováno v:
TIME
We describe a method for spatio-temporal data mining based on expected distribution domain generalization (ExGen) graphs. Using familiar calendar and geographical concepts, such as workdays, weeks, climatic regions, and countries, spatio-temporal dat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f3482c7c7e35274631a87d201b62afcc
https://doi.org/10.1109/time.2003.1214895
https://doi.org/10.1109/time.2003.1214895
Publikováno v:
TIME
The paper addresses the problem of generalizing temporal data based on calendar (date and time) attributes The proposed method is based on a domain generalization graph, i.e., a lattice defining a partial order that represents a set of generalization
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::283222ef7d3102b1619b1b701b65d466
https://doi.org/10.1109/time.1998.674148
https://doi.org/10.1109/time.1998.674148
Autor:
Howard J. Hamilton, Dee Jay Randall
Publikováno v:
Temporal, Spatial, and Spatio-Temporal Data Mining ISBN: 9783540417736
TSDM
TSDM
This paper addresses the problem of data mining from temporal data based on calendar (date and time) attributes. The proposed methods uses a probabilistic domain generalization graph, i.e., a graph defining a partial order that represents a set of ge
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a307b7e5315b1ee600be6b10bec1018a
https://doi.org/10.1007/3-540-45244-3_10
https://doi.org/10.1007/3-540-45244-3_10
Autor:
Howard J. Hamilton, Dee Jay Randall
Publikováno v:
Multiple Approaches to Intelligent Systems ISBN: 9783540660767
IEA/AIE
IEA/AIE
We introduce techniques for heuristically ranking aggregations of data. We assume that the possible aggregations for each attribute are specified by a domain generalization graph. For temporal attributes containing dates and times, a calendar domain
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3f537dcc1fee4418d1f3a01311dd2c1f
https://doi.org/10.1007/978-3-540-48765-4_76
https://doi.org/10.1007/978-3-540-48765-4_76
Publikováno v:
Principles of Data Mining and Knowledge Discovery ISBN: 9783540650683
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::59f18bf349526c5349a05c540140f0aa
https://doi.org/10.1007/bfb0094835
https://doi.org/10.1007/bfb0094835