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» Phenomenal Data Mining: From Data to Phenomena
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ICDM
2006
IEEE
118views Data Mining» more  ICDM 2006»
14 years 3 months ago
Reducing the Frequent Pattern Set
One of the major problems in frequent pattern mining is the explosion of the number of results, making it difficult to identify the interesting frequent patterns. In a recent pap...
Ronnie Bathoorn, Arne Koopman, Arno Siebes
SDM
2009
SIAM
192views Data Mining» more  SDM 2009»
14 years 6 months ago
Mining Cohesive Patterns from Graphs with Feature Vectors.
The increasing availability of network data is creating a great potential for knowledge discovery from graph data. In many applications, feature vectors are given in addition to g...
Arash Rafiey, Flavia Moser, Martin Ester, Recep Co...
ICDM
2005
IEEE
189views Data Mining» more  ICDM 2005»
14 years 2 months ago
Integrating Hidden Markov Models and Spectral Analysis for Sensory Time Series Clustering
We present a novel approach for clustering sequences of multi-dimensional trajectory data obtained from a sensor network. The sensory time-series data present new challenges to da...
Jie Yin, Qiang Yang
KDD
2006
ACM
134views Data Mining» more  KDD 2006»
14 years 9 months ago
Identifying bridging rules between conceptual clusters
1 A bridging rule in this paper has its antecedent and action from different conceptual clusters. We first design two algorithms for mining bridging rules between clusters in a dat...
Shichao Zhang, Feng Chen, Xindong Wu, Chengqi Zhan...
SDM
2007
SIAM
147views Data Mining» more  SDM 2007»
13 years 10 months ago
Constraint-Based Pattern Set Mining
Local pattern mining algorithms generate sets of patterns, which are typically not directly useful and have to be further processed before actual application or interpretation. Ra...
Luc De Raedt, Albrecht Zimmermann