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» Scalable mining of large disk-based graph databases
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ICTAI
2003
IEEE
14 years 25 days ago
Parallel Mining of Maximal Frequent Itemsets from Databases
In this paper, we propose a parallel algorithm for mining maximal frequent itemsets from databases. A frequent itemset is maximal if none of its supersets is frequent. The new par...
Soon Myoung Chung, Congnan Luo
JCP
2008
171views more  JCP 2008»
13 years 7 months ago
Mining Frequent Subgraph by Incidence Matrix Normalization
Existing frequent subgraph mining algorithms can operate efficiently on graphs that are sparse, have vertices with low and bounded degrees, and contain welllabeled vertices and edg...
Jia Wu, Ling Chen
KDD
2005
ACM
127views Data Mining» more  KDD 2005»
14 years 1 months ago
Mining closed relational graphs with connectivity constraints
Relational graphs are widely used in modeling large scale networks such as biological networks and social networks. In this kind of graph, connectivity becomes critical in identif...
Xifeng Yan, Xianghong Jasmine Zhou, Jiawei Han
PVLDB
2010
146views more  PVLDB 2010»
13 years 2 months ago
HaLoop: Efficient Iterative Data Processing on Large Clusters
The growing demand for large-scale data mining and data analysis applications has led both industry and academia to design new types of highly scalable data-intensive computing pl...
Yingyi Bu, Bill Howe, Magdalena Balazinska, Michae...
CIKM
2001
Springer
13 years 11 months ago
SQL Database Primitives for Decision Tree Classifiers
Scalable data mining in large databases is one of today's challenges to database technologies. Thus, substantial effort is dedicated to a tight coupling of database and data ...
Kai-Uwe Sattler, Oliver Dunemann