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» Mining Very Large Databases
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VLDB
1998
ACM
112views Database» more  VLDB 1998»
14 years 2 months ago
Incremental Clustering for Mining in a Data Warehousing Environment
Data warehouses provide a great deal of opportunities for performing data mining tasks such as classification and clustering. Typically, updates are collected and applied to the d...
Martin Ester, Hans-Peter Kriegel, Jörg Sander...
FPL
2008
Springer
122views Hardware» more  FPL 2008»
13 years 11 months ago
Mining Association Rules with systolic trees
Association Rules Mining (ARM) algorithms are designed to find sets of frequently occurring items in large databases. ARM applications have found their way into a variety of field...
Song Sun, Joseph Zambreno
KDD
2005
ACM
103views Data Mining» more  KDD 2005»
14 years 10 months ago
Fast discovery of unexpected patterns in data, relative to a Bayesian network
We consider a model in which background knowledge on a given domain of interest is available in terms of a Bayesian network, in addition to a large database. The mining problem is...
Szymon Jaroszewicz, Tobias Scheffer
ICDM
2008
IEEE
222views Data Mining» more  ICDM 2008»
14 years 4 months ago
GRAPHITE: A Visual Query System for Large Graphs
We present Graphite, a system that allows the user to visually construct a query pattern, finds both its exact and approximate matching subgraphs in large attributed graphs, and ...
Duen Horng Chau, Christos Faloutsos, Hanghang Tong...
JIIS
2000
111views more  JIIS 2000»
13 years 9 months ago
Multidimensional Index Structures in Relational Databases
Abstract. Efficient query processing is one of the basic needs for data mining algorithms. Clustering algorithms, association rule mining algorithms and OLAP tools all rely on effi...
Christian Böhm, Stefan Berchtold, Hans-Peter ...