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KDD
2009
ACM
163views Data Mining» more  KDD 2009»
14 years 8 months ago
Large-scale graph mining using backbone refinement classes
We present a new approach to large-scale graph mining based on so-called backbone refinement classes. The method efficiently mines tree-shaped subgraph descriptors under minimum f...
Andreas Maunz, Christoph Helma, Stefan Kramer
BIBM
2007
IEEE
133views Bioinformatics» more  BIBM 2007»
13 years 8 months ago
Mining Clinical Data with a Temporal Dimension: A Case Study
Clinical databases store large amounts of information about patients and their medical conditions. Data mining techniques can extract relationships and patterns holding in this we...
Michele Berlingerio, Francesco Bonchi, Fosca Giann...
KDD
2001
ACM
163views Data Mining» more  KDD 2001»
14 years 8 months ago
The "DGX" distribution for mining massive, skewed data
Skewed distributions appear very often in practice. Unfortunately, the traditional Zipf distribution often fails to model them well. In this paper, we propose a new probability di...
Zhiqiang Bi, Christos Faloutsos, Flip Korn
SIGMOD
1997
ACM
134views Database» more  SIGMOD 1997»
14 years 2 days ago
Scalable Parallel Data Mining for Association Rules
One of the important problems in data mining is discovering association rules from databases of transactions where each transaction consists of a set of items. The most time consu...
Eui-Hong Han, George Karypis, Vipin Kumar
CORR
2010
Springer
138views Education» more  CORR 2010»
13 years 8 months ago
Data Stream Clustering: Challenges and Issues
Very large databases are required to store massive amounts of data that are continuously inserted and queried. Analyzing huge data sets and extracting valuable pattern in many appl...
Madjid Khalilian, Norwati Mustapha