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ICTAI
2003
IEEE
14 years 1 months 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
APWEB
2003
Springer
13 years 11 months ago
Mining "Hidden Phrase" Definitions from the Web
Keyword searching is the most common form of document search on the Web. Many Web publishers manually annotate the META tags and titles of their pages with frequently queried phras...
Hung V. Nguyen, P. Velamuru, Deepak Kolippakkam, H...
ASC
2011
13 years 2 months ago
A rough set approach to multiple dataset analysis
In the area of data mining, the discovery of valuable changes and connections (e.g., causality) from multiple data sets has been recognized as an important issue. This issue essen...
Ken Kaneiwa
ICDM
2010
IEEE
217views Data Mining» more  ICDM 2010»
13 years 5 months ago
Discovering Temporal Features and Relations of Activity Patterns
An important problem that arises during the data mining process in many new emerging application domains is mining data with temporal dependencies. One such application domain is a...
Ehsan Nazerfard, Parisa Rashidi, Diane J. Cook
CLIMA
2004
13 years 9 months ago
The Apriori Stochastic Dependency Detection (ASDD) Algorithm for Learning Stochastic Logic Rules
Apriori Stochastic Dependency Detection (ASDD) is an algorithm for fast induction of stochastic logic rules from a database of observations made by an agent situated in an environm...
Christopher Child, Kostas Stathis