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SDM
2012
SIAM
289views Data Mining» more  SDM 2012»
13 years 20 hour ago
Mining Compressing Sequential Patterns
Compression based pattern mining has been successfully applied to many data mining tasks. We propose an approach based on the minimum description length principle to extract seque...
Hoang Thanh Lam, Fabian Moerchen, Dmitriy Fradkin,...
KDD
2004
ACM
211views Data Mining» more  KDD 2004»
15 years 10 months ago
Towards parameter-free data mining
Most data mining algorithms require the setting of many input parameters. Two main dangers of working with parameter-laden algorithms are the following. First, incorrect settings ...
Eamonn J. Keogh, Stefano Lonardi, Chotirat (Ann) R...
KDD
1998
ACM
160views Data Mining» more  KDD 1998»
15 years 1 months ago
Algorithms for Characterization and Trend Detection in Spatial Databases
1 The number and the size of spatial databases, e.g. for geomarketing, traffic control or environmental studies, are rapidly growing which results in an increasing need for spatial...
Martin Ester, Alexander Frommelt, Hans-Peter Krieg...
SDM
2012
SIAM
293views Data Mining» more  SDM 2012»
13 years 20 hour ago
RP-growth: Top-k Mining of Relevant Patterns with Minimum Support Raising
One practical inconvenience in frequent pattern mining is that it often yields a flood of common or uninformative patterns, and thus we should carefully adjust the minimum suppor...
Yoshitaka Kameya, Taisuke Sato
DAWAK
2005
Springer
14 years 11 months ago
Incremental Data Mining Using Concurrent Online Refresh of Materialized Data Mining Views
Abstract. Data mining is an iterative process. Users issue series of similar data mining queries, in each consecutive run slightly modifying either the definition of the mined dat...
Mikolaj Morzy, Tadeusz Morzy, Marek Wojciechowski,...