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Data mining: rule mining algorithms


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Table of contents

Data mining: rule mining algorithms

Introduction /1

Introduction /2

ARM /1 (association rules mining)

ARM /2

ARM /3

ARM /4

ARM /5

ARM /6

ARM /7

Quantitative rules mining

Sequential mining /1

Sequential mining /2

Sequential mining /3

Posets /1

Posets /2

Posets /3

Lattices /1

Lattices /2

Lattices /3

Algorithmic families /1

Algorithmic families /2

Apriori /1

Apriori /2

Apriori /3

Apriori /4

Apriori /5

Apriori /6

Partition /1

Partition /2

FP-growth /1

FP-growth /2

FP-growth /3

FP-growth /4

FP-growth /5

Graphs /1

Graphs /2

Graphs /3

Graphs /4

Graphs /5

Max clique /1

Max clique /2

Max clique /3

Max clique /4

Closure operators/systems

Formal Concept Analysis /1

Formal Concept Analysis /2

Formal Concept Analysis /3

Formal Concept Analysis /4

Formal Concept Analysis /5

Formal Concept Analysis /6

Formal Concept Analysis /7

A-Close /1

A-Close /2

A-Close /3

A-Close /4

A-Close /5

A-Close /6

CHARM

Parallel algorithms

Summary

Bibliography

Author: Roberto Innocente

E-mail: rinnocente@eurohpc.org

Compressed postscript: dm.ps.gz

Pdf : dm.pdf

Author: Roberto Innocente