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SDM
2009
SIAM
192views Data Mining» more  SDM 2009»
14 years 25 days 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...
SDM
2009
SIAM
225views Data Mining» more  SDM 2009»
14 years 25 days ago
Integrated KL (K-means - Laplacian) Clustering: A New Clustering Approach by Combining Attribute Data and Pairwise Relations.
Most datasets in real applications come in from multiple sources. As a result, we often have attributes information about data objects and various pairwise relations (similarity) ...
Fei Wang, Chris H. Q. Ding, Tao Li
SDM
2009
SIAM
123views Data Mining» more  SDM 2009»
14 years 25 days ago
Randomization Techniques for Graphs.
Mining graph data is an active research area. Several data mining methods and algorithms have been proposed to identify structures from graphs; still, the evaluation of those resu...
Gemma C. Garriga, Kai Puolamäki, Sami Hanhij&...
SDM
2009
SIAM
111views Data Mining» more  SDM 2009»
14 years 25 days ago
A New Constraint for Mining Sets in Sequences.
Discovering interesting patterns in event sequences is a popular task in the field of data mining. Most existing methods try to do this based on some measure of cohesion to deter...
Bart Goethals, Boris Cule, Céline Robardet
SDM
2009
SIAM
126views Data Mining» more  SDM 2009»
14 years 25 days ago
An Entity Based Model for Coreference Resolution.
Recently, many advanced machine learning approaches have been proposed for coreference resolution; however, all of the discriminatively-trained models reason over mentions rather ...
Michael L. Wick, Aron Culotta, Khashayar Rohaniman...
SDM
2009
SIAM
143views Data Mining» more  SDM 2009»
14 years 25 days ago
Finding Representative Association Rules from Large Rule Collections.
One of the most well-studied problems in data mining is computing association rules from large transactional databases. Often, the rule collections extracted from existing datamin...
Warren L. Davis IV, Peter Schwarz, Evimaria Terzi
SDM
2009
SIAM
176views Data Mining» more  SDM 2009»
14 years 25 days ago
Constraint-Based Subspace Clustering.
In high dimensional data, the general performance of traditional clustering algorithms decreases. This is partly because the similarity criterion used by these algorithms becomes ...
Élisa Fromont, Adriana Prado, Céline...
SDM
2009
SIAM
112views Data Mining» more  SDM 2009»
14 years 25 days ago
A Re-evaluation of the Over-Searching Phenomenon in Inductive Rule Learning.
Most commonly used inductive rule learning algorithms employ a hill-climbing search, whereas local pattern discovery algorithms employ exhaustive search. In this paper, we evaluat...
Frederik Janssen, Johannes Fürnkranz
SDM
2009
SIAM
161views Data Mining» more  SDM 2009»
14 years 25 days ago
Polynomial-Delay and Polynomial-Space Algorithms for Mining Closed Sequences, Graphs, and Pictures in Accessible Set Systems.
In this paper, we study efficient closed pattern mining in a general framework of set systems, which are families of subsets ordered by set-inclusion with a certain structure, pro...
Hiroki Arimura, Takeaki Uno
SDM
2009
SIAM
157views Data Mining» more  SDM 2009»
14 years 25 days ago
MUSK: Uniform Sampling of k Maximal Patterns.
Recent research in frequent pattern mining (FPM) has shifted from obtaining the complete set of frequent patterns to generating only a representative (summary) subset of frequent ...
Mohammad Al Hasan, Mohammed Javeed Zaki