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  • Knowledge Discovery in DatabaseData Mining


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KDD

  • KDD1989IJCAI-89 Workshop

  • 1995KDDKDD95

  • Kluwers Publishers1997Knowledge Discovery and Data Mining


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1988

Expert Systems

1990

Expert Systems

1995

2004


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KDD

  • KDD

  • KDD


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  • ,

  • /


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100


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GUS

3.8%


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  • (ABA)14.9


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  • Mellon

  • Firstar


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30


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Data Mining

Knowledge Discovery in Databases


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  • OLAPwhat happenedOLAPWhat nextWhat ifOLAP

  • OLAP

  • OLAPOLAPOLAP


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    • Knowledge Discovery from/in Database, KDD

    • Knowledge extract

    • /Data / Model analysis


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  • Data Mining


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  • Fayyad

  • KDD


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  • WWW


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1

2

50%-90%

a)

b)

c)


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d)

e)

f)

g)

h)

3

4

4

a); b); c); d)


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5

a)

b)

c)


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6

a)

b)

3%17%


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7

OLAP


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KDD


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KDD

  • 1.KDD

  • 2.


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KDD

  • 3.2

  • 4.


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KDD

  • 5.KDDKDDKDD

  • 6.


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KDD

  • 7.KDD

  • 8.


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KDD

  • 9.

  • KDD


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/

  • / (class / concept description)

  • (data characterization)

  • (Data discrimination)


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1 (association analysis)

(association rule) X Y

A1 A2 Am B1 B2 Bn

multi-dimensional association rule(single-dimensional association rule)

2

age(x, 20..29) income(X, 20K..29K)

buys(X, CD_player) [support = 2%, confidence = 60%]


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1

(classification)

2

IF-THEN

3 (relevance analysis)


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1

(clustering)

2


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1

(outlier)

(outlier mining)

2


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1

(evolution analysis)

a)

b)

c)


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1SPSS5A(Assess)(Access)(Analyze)(Act)(Automate)

(2)SASSEMMA(Sample)(Explore)(Modify)(Model)(Assess)

(3) CRISP-DMCRISP-DM

(4) Two CrowsCRISP-DM


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KDD


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  • Web

  • Web


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    • SASEnterprise Miner

    • IBMIntelligent Miner

    • SGISetMiner

    • SPSSClementine

    • SybaseWarehouse Studio

    • RuleQuest ResearchSee5

    • CoverStoryEXPLORAKnowledge Discovery WorkbenchDBMinerQuest


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/

intranet/extranet

web

/


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    • vector-valued data

    • Salford SystemsCART(www.salford-systems.com)


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CBA


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  • data mining schemaDMQL


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    • DBMS

    • data mining schemaDMQL

    • DBMinerDMQL


Dbminer

DBMiner


Sas enterprise miner

SAS Enterprise Miner


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  • Internet/Extranetfirst class


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    • Internet/Extranet


Spss clementine

SPSS Clementine

PMML


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  • ubiquitous


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    • ubiquitous

      PKDD2001KarguptaKarguptaUniversity of Maryland Baltimore CountyCAREER2001420064Ubiquitous


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  • IBM Intelligent Score Service


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  • OLAPPMMLPMML


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  • PMML


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  • ODBC


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    • embedded technology


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Rough set

Rough Set

  • Z.Pawlak1982VaguenessUncertainty


Clustering

Clustering

  • ClusteringCluster


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  • Agrawal

  • AISSETMR.AgrawalApriori

  • Apriori


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  • L.A.Zadeh1965


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  • SVMSVM


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y

Y1

y = x + 1

Y1

x

X1


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IV.

:

  • ACM SIGMOD: Intl. Conf. on Management of Data

  • VLDB / PODS: Intl. Conf. on Very Large Data Bases

  • ICDE: Intl. Conf. on Data Engineering

  • SIGKDD: Intl. Conf. on Knowledge Discovery and Data Mining

    :

  • SIGKDD, ICDM, SDM, PKDD, PAKDD


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DM

  • DMKD (DAMI): Data Mining and Knowledge Discovery

  • TKDE: IEEE Transaction on Knowledge and Data Engineering

  • TKDD: ACM Transaction on KDD

  • SIGKDD Explorations


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[1] Jiawei Han, Micheline Kamber. , . : . , 2001.

(Data Mining: Concepts and Techniques (Second Edition)200511)

[2] Jiawei Han. Data Mining: Principles & Research Frontiers (PPT). May 23-27, 2005. http://www.cs.uiuc.edu/~hanj

[3] David Hand . . . , 2003.

[4]Pangning Tan, Michael Steinbach. Intorduction to Data Mining. . 2006


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