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HIPC
2003
Springer
15 years 2 months ago
Parallel and Distributed Frequent Itemset Mining on Dynamic Datasets
Traditional methods for data mining typically make the assumption that data is centralized and static. This assumption is no longer tenable. Such methods waste computational and I/...
Adriano Veloso, Matthew Eric Otey, Srinivasan Part...
SDM
2009
SIAM
170views Data Mining» more  SDM 2009»
15 years 6 months ago
Mining Complex Spatio-Temporal Sequence Patterns.
Mining sequential movement patterns describing group behaviour in potentially streaming spatio-temporal data sets is a challenging problem. Movements are typically noisy and often...
Florian Verhein
IDEAS
1999
IEEE
175views Database» more  IDEAS 1999»
15 years 1 months ago
A Parallel Scalable Infrastructure for OLAP and Data Mining
Decision support systems are important in leveraging information present in data warehouses in businesses like banking, insurance, retail and health-care among many others. The mu...
Sanjay Goil, Alok N. Choudhary
KDD
2004
ACM
126views Data Mining» more  KDD 2004»
15 years 10 months ago
Dense itemsets
Frequent itemset mining has been the subject of a lot of work in data mining research ever since association rules were introduced. In this paper we address a problem with frequen...
Heikki Mannila, Jouni K. Seppänen
KDD
2002
ACM
140views Data Mining» more  KDD 2002»
15 years 10 months ago
Mining frequent item sets by opportunistic projection
In this paper, we present a novel algorithm OpportuneProject for mining complete set of frequent item sets by projecting databases to grow a frequent item set tree. Our algorithm ...
Junqiang Liu, Yunhe Pan, Ke Wang, Jiawei Han