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» Mining interesting sets and rules in relational databases
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KDD
1998
ACM
105views Data Mining» more  KDD 1998»
13 years 12 months ago
PlanMine: Sequence Mining for Plan Failures
This paper presents the PLANMINE sequence mining algorithm to extract patterns of events that predict failures in databases of plan executions. New techniques were needed because ...
Mohammed Javeed Zaki, Neal Lesh, Mitsunori Ogihara
AIR
2000
91views more  AIR 2000»
13 years 7 months ago
PlanMine: Predicting Plan Failures Using Sequence Mining
This paper presents the PLANMINE sequence mining algorithm to extract patterns of events that predict failures in databases of plan executions. New techniques were needed because p...
Mohammed Javeed Zaki, Neal Lesh, Mitsunori Ogihara
ASC
2011
13 years 2 months ago
Fuzzy sets in machine learning and data mining
Machine learning, data mining, and several related research areas are concerned with methods for the automated induction of models and the extraction of interesting patterns from ...
Eyke Hüllermeier
KDD
1998
ACM
131views Data Mining» more  KDD 1998»
13 years 12 months ago
Interestingness-Based Interval Merger for Numeric Association Rules
We present an algorithm for mining association rules from relational tables containing numeric and categorical attributes. The approach is to merge adjacent intervals of numeric v...
Ke Wang, Soon Hock William Tay, Bing Liu
TFS
2011
242views Education» more  TFS 2011»
13 years 2 months ago
Linguistic Summarization Using IF-THEN Rules and Interval Type-2 Fuzzy Sets
—Linguistic summarization (LS) is a data mining or knowledge discovery approach to extract patterns from databases. Many authors have used this technique to generate summaries li...
Dongrui Wu, Jerry M. Mendel