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» Mining interesting sets and rules in relational databases
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VLDB
2004
ACM
97views Database» more  VLDB 2004»
14 years 2 months ago
CHICAGO: A Test and Evaluation Environment for Coarse-Grained Optimization
Relational OLAP tools and other database applications generate sequences of SQL statements that are sent to the database server as result of a single information request issued by...
Tobias Kraft, Holger Schwarz
KDD
2002
ACM
136views Data Mining» more  KDD 2002»
14 years 9 months ago
Relational Markov models and their application to adaptive web navigation
Relational Markov models (RMMs) are a generalization of Markov models where states can be of different types, with each type described by a different set of variables. The domain ...
Corin R. Anderson, Pedro Domingos, Daniel S. Weld
CIKM
2010
Springer
13 years 7 months ago
Partial drift detection using a rule induction framework
The major challenge in mining data streams is the issue of concept drift, the tendency of the underlying data generation process to change over time. In this paper, we propose a g...
Damon Sotoudeh, Aijun An
KDD
2007
ACM
184views Data Mining» more  KDD 2007»
14 years 9 months ago
Correlation search in graph databases
Correlation mining has gained great success in many application domains for its ability to capture the underlying dependency between objects. However, the research of correlation ...
Yiping Ke, James Cheng, Wilfred Ng
CORR
2010
Springer
138views Education» more  CORR 2010»
13 years 9 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