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KDD
2002
ACM
171views Data Mining» more  KDD 2002»
14 years 7 months ago
Mining complex models from arbitrarily large databases in constant time
In this paper we propose a scaling-up method that is applicable to essentially any induction algorithm based on discrete search. The result of applying the method to an algorithm ...
Geoff Hulten, Pedro Domingos
KDD
1999
ACM
185views Data Mining» more  KDD 1999»
13 years 11 months ago
User-Driven Navigation Pattern Discovery from Internet Data
Managers of electronic commerce sites need to learn as much as possible about their customers and those browsing their virtual premises, in order to maximise the return on marketin...
Matthias Baumgarten, Alex G. Büchner, Sarabjo...
SPIN
2012
Springer
11 years 10 months ago
Counterexample Explanation by Anomaly Detection
Since counterexamples generated by model checking tools are only symptoms of faults in the model, a significant amount of manual work is required in order to locate the fault that...
Stefan Leue, Mitra Tabaei Befrouei
ICDE
2005
IEEE
146views Database» more  ICDE 2005»
14 years 8 months ago
Mining Evolving Customer-Product Relationships in Multi-Dimensional Space
Previous work on mining transactional database has focused primarily on mining frequent itemsets, association rules, and sequential patterns. However, interesting relationships be...
Xiaolei Li, Jiawei Han, Xiaoxin Yin, Dong Xin
SIGMOD
2010
ACM
196views Database» more  SIGMOD 2010»
13 years 7 months ago
GAIA: graph classification using evolutionary computation
Discriminative subgraphs are widely used to define the feature space for graph classification in large graph databases. Several scalable approaches have been proposed to mine disc...
Ning Jin, Calvin Young, Wei Wang