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    TABLE OF CONTENTS

    CHAPTER NO. TITLE PAGE NO.

    ABSTRACT ivLIST OF TABLES xii

    LIST OF FIGURES xiv

    LIST OF ABBREVIATIONS xvii

    1 INTRODUCTION 1

    1.1GENERAL

    1.2 DATA MINING 1

    1.3 ASSOCIATION RULE MINING 4

    1.4 POPULATION BASED STOCHASTIC SEARCHMETHODS 5

    1.5 PROBLEM IDENTIFICATION 7

    1.6 OBJECTIE OF THE RESEARCH !

    1.7 RESEARCH APPROACH "

    1.! ORGANI#ATION OF THE THESIS 1$

    2 LITERTURE REVIEW 12

    2.1 GENERAL 12

    2.1 TRADITIONAL METHODS FOR MINING

    ASSOCIATION RULES 122.2.1 AIS A%&'(i)*+ 12

    2.2.2 A,(i'(i -/ A,(i'(i0B-/ A%&'(i)*+ 13

    2.2.3 FP0T( -/ FP0G(')*FP0T( B-/ A%&'(i)*+ 14

    2.2.4 O)*( A'i-)i' R% Mii& M)*'/ 15

    2.2 STOCHASTIC METHODS FOR MINING ASSOCIATION

    RULES 16

    2.3.1 G)i A%&'(i)*+ '( ARM

    2.3.2 P-()i% S-(+ O,)i+i8-)i' '( ARM 21

    2.3 H9BRID APPROACHES OF GA AND PSO 232.4 MEMETIC PARTICLE S:ARM OPTIMI#ATION 25 2.6

    SUMMAR9 2!

    3 CONCEPTS AND PROBLEM SETTINGS

    2"

    3.1 AIMS OF THIS CHAPTER 2"

    3.2 STOCHASTIC SEARCH METHODS 2"

    3.3 OERIE: OF EOLUTIONAR9 COMPUTING 31 3.3.1 G)i A%&'(i)*+ 35

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    3.3.2 P-()i% S-(+ O,)i+i8-)i' 3!

    3.4 DATASETS USED IN THIS STUD9 41

    3.5 PERFORMANCE EALUATION 42

    3.6 SUMMAR9 44

    4 ASSOCIATION RULE MINING USING GENETIC

    ALGORITHM 45

    4.1 AIMS OF THIS CHAPTER 45

    4.2 NEED AND MOTIATION 45

    4.3 MINING ARM USING GA 46

    4.3.1 Ex,(i+)-% S), 46

    4.3.2 R%) -/ Dii' 4"

    4.4 EFFECTIE PARAMETER SETTING OF GA FOR ARM 52

    4.4.1 M)*'/'%'&; 54

    4.4.2 Ex,(i+)-% R%) -/ Dii' 55

    4.5 SUMMAR9 5"

    5 GENETIC ALGORITHM BASED ASSOCIATION RULEMINING 61

    5.1 AIMS OF THIS CHAPTER 61

    5.2 GA :ITH ELITISM FOR ARM 61

    5.2.1 E%i)i+ i GA 62

    5.2.2 Ex,(i+)-% R%) -/ Dii' 645.3 ADAPTIE GA FOR ARM 6"

    5.3.1 N/ '( A/-,)i' 6"

    5.3.2 Ex,(i+)-% R%) -/ Dii' 72

    5.4 SUMMAR9 75

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    6 PARTICLE SWARM OPTIMIZATION FOR MINING

    ASSOCIATION RULES 76

    6.1 AIMS OF THIS CHAPTER 766.2 PSO FOR ARM 76

    6.2.1 M)*'/'%'&; 77

    6.3.2 Ex,(i+)-% R%) -/ Dii' !$

    6.3 CHAOTIC PSO FOR ARM !4

    6.3.1 C*-')i+ i PSO !5

    6.3.2 Ex,(i+)-% R%) -/ Dii' !6

    6.4 D9NAMIC NEIGHBORHOOD SELECTION IN PSOFOR ARM !"

    6.4.1 D;-+i Ni&*

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    ". CONCLUSIONS AND FUTURE WOR 143

    ".1 AIMS OF THIS CHAPTER 143

    ".2 SUMMAR9 143

    ".2 SCOPE FOR FUTURE :OR> 144

    REFERENCES 145

    LIST OF PUBLICATIONS 163

    VITAE 166

    ANNE!URE I 167

    LIST OF TABLES

    TABLE NO. TITLE PAGE NO.

    3.1 D(i,)i' ' )* D-)-) U/ 42

    4.1 GA P-(-+)( '( ARM 5$

    4.2 P(/i)iv A(-; '( ARM i)* GA 5$

    4.3 N'. ' R% G(-)/

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    '( ARM 1$1

    7.3 C%-ii-)i' i)' S)-)

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    LIST OF FIGURES

    FIGURE NO. TITLE PAGE NO.

    3.1 B%'@ Di-&(-+ ' G)i A%&'(i)*+ 36

    3.2 P/'0'/ '( i+,% GA 36

    3.3 C(''v( O,(-)'( 3!

    3.4 P/'0'/ '( i+,% PSO 3"

    3.5 Di,%-+) ' - ,-()i% 41

    4.1 R'%)) :*% S%)i' M)*'/'%'&; 4!

    4.2 F%'*-() ' i+,% GA 55

    4.3 P',%-)i' Si8 A(-; '( ARM i)* GA 56

    4.4 Mii++ S,,'() -/ C'i/ A(-; '(

    ARM i)* GA 5"

    5.1 E%i)i+ i M%)i'

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    6.7 C'v(& (-) ' CPSO '( ARM !!

    6.! PSO -%&'(i)*+ '( -'i-)i' (% +ii& i)* D;-+i

    Ni&*

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    !.! Fi) -% '( PSO i)* SFLA '( ARM 14$

    !." C'+,-(i' ' )* P(/i)iv A(-; '( ARM 141

    !.1$ C'+,-(i' ' )* N'. ' (% &(-)/ i ARM

    141

    LIST OF ABBREVIATIONS

    ACO 0 A) C'%'; O,)i+i8-)i'

    AGA 0 A/-,)iv G)i A%&'(i)*+

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    APSO 0 A/-,)iv P-()i% S-(+ O,)i+i8-)i'

    APSOSFLA 0 A/-,)iv P-()i% S-(+ O,)i+i8-)i' i)* S*%/ F('&

    L-,i& A%&'(i)*+

    AR 0 A'i-)i' R%

    ARM 0 A'i-)i' R% Mii&

    CPSO 0 C*-')i P-()i% S-(+ O,)i+i8-)i'

    EA 0 Ev'%)i'-(; A%&'(i)*+

    EC 0 Ev'%)i'-(; C'+,)i&

    FP 0 F() P-))(

    GA 0 G)i A%&'(i)*+

    GPSO 0 GAPSO H;