SlideShare ist ein Scribd-Unternehmen logo
1 von 32
Disjoint Sets Data Structure (Chap. 21) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Multiple Operations ,[object Object],[object Object],[object Object],[object Object]
An Application of Disjoint-Set ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Linked-List Implementation ,[object Object],[object Object],[object Object],[object Object]
Linked-lists for two sets head tail g head tail c head Set { c , h , e } Set { f ,  g } UNION of  two Sets e tail c h e f f g h
UNION Implementation ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Weighted-Union Heuristic ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Disjoint-set Implementation: Forests  ,[object Object],d d h e c c Set { c , h , e } Set { f , d } UNION c f h e c c c f
Straightforward Solution ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Union by Rank & Path Compression ,[object Object],[object Object]
Path Compression f e d c f e d c
Algorithm for Disjoint-Set Forest ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Worst case running time for  m  MAKE-SET, UNION, FIND-SET operations is: O ( m  ( n ))  where   ( n )  4. So nearly linear in  m . UNION( x , y ) 1. LINK(FIND-SET( x ),FIND-SET( y ))
Analysis of Union by Rank with Path Compression (by amortized analysis) ,[object Object],[object Object],[object Object],[object Object]
A very quickly growing function and its inverse ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Quickness of Function A k ( j )’s Increase ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
How Quick A k ( j ) Increase ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Inverse of A k ( n ):  ( n )  ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
O ( m  ( n )) bound: Property of Ranks ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
O ( m  ( n )) bound proof ,[object Object],[object Object],[object Object],[object Object],[object Object]
Potential Function ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
level( x ) and iter( x ) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Relations among  rank [ p [ x ]], level( x ) and iter( x ) ,[object Object],[object Object]
Properties for Potential Function   q ( x )  ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Potential Changes of Operations ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Amortized Costs of Operations ,[object Object],[object Object],[object Object]
Amortized Costs of Operations (cont.) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Amortized Costs of Operations (cont.) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Proof of Lemma 21.12 (cont.) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Proof of Lemma 21.12 (cont.) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Upper bound for Disjoint-sets ,[object Object],[object Object]
Summary  ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
A typical example using Disjoint Set ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Weitere ähnliche Inhalte

Was ist angesagt? (20)

Minimum spanning tree
Minimum spanning treeMinimum spanning tree
Minimum spanning tree
 
Data Structures : hashing (1)
Data Structures : hashing (1)Data Structures : hashing (1)
Data Structures : hashing (1)
 
Red black tree
Red black treeRed black tree
Red black tree
 
Threaded Binary Tree
Threaded Binary TreeThreaded Binary Tree
Threaded Binary Tree
 
Selection sorting
Selection sortingSelection sorting
Selection sorting
 
Graph traversals in Data Structures
Graph traversals in Data StructuresGraph traversals in Data Structures
Graph traversals in Data Structures
 
Binary search tree(bst)
Binary search tree(bst)Binary search tree(bst)
Binary search tree(bst)
 
Analysis of algorithm
Analysis of algorithmAnalysis of algorithm
Analysis of algorithm
 
Divide and conquer
Divide and conquerDivide and conquer
Divide and conquer
 
Trees, Binary Search Tree, AVL Tree in Data Structures
Trees, Binary Search Tree, AVL Tree in Data Structures Trees, Binary Search Tree, AVL Tree in Data Structures
Trees, Binary Search Tree, AVL Tree in Data Structures
 
Lecture optimal binary search tree
Lecture optimal binary search tree Lecture optimal binary search tree
Lecture optimal binary search tree
 
AVL Tree
AVL TreeAVL Tree
AVL Tree
 
Data structure - Graph
Data structure - GraphData structure - Graph
Data structure - Graph
 
Data Structure (Tree)
Data Structure (Tree)Data Structure (Tree)
Data Structure (Tree)
 
Bfs and Dfs
Bfs and DfsBfs and Dfs
Bfs and Dfs
 
SINGLE-SOURCE SHORTEST PATHS
SINGLE-SOURCE SHORTEST PATHS SINGLE-SOURCE SHORTEST PATHS
SINGLE-SOURCE SHORTEST PATHS
 
Backtracking
BacktrackingBacktracking
Backtracking
 
Binary Search Tree
Binary Search TreeBinary Search Tree
Binary Search Tree
 
Breadth First Search & Depth First Search
Breadth First Search & Depth First SearchBreadth First Search & Depth First Search
Breadth First Search & Depth First Search
 
Dinive conquer algorithm
Dinive conquer algorithmDinive conquer algorithm
Dinive conquer algorithm
 

Andere mochten auch

Sets and disjoint sets union123
Sets and disjoint sets union123Sets and disjoint sets union123
Sets and disjoint sets union123Ankita Goyal
 
Advanced Algorithms #1 - Union/Find on Disjoint-set Data Structures.
Advanced Algorithms #1 - Union/Find on Disjoint-set Data Structures.Advanced Algorithms #1 - Union/Find on Disjoint-set Data Structures.
Advanced Algorithms #1 - Union/Find on Disjoint-set Data Structures.Andrea Angella
 
Set data structure
Set data structure Set data structure
Set data structure Tech_MX
 
Set Operations - Union Find and Bloom Filters
Set Operations - Union Find and Bloom FiltersSet Operations - Union Find and Bloom Filters
Set Operations - Union Find and Bloom FiltersAmrinder Arora
 
Time complexity of union find
Time complexity of union findTime complexity of union find
Time complexity of union findWei (Terence) Li
 
lecture 21
lecture 21lecture 21
lecture 21sajinsc
 
Set data structure 2
Set data structure 2Set data structure 2
Set data structure 2Tech_MX
 
Effective Semantic Web Service Composition Framework Based on QoS
Effective Semantic Web Service Composition Framework Based on QoSEffective Semantic Web Service Composition Framework Based on QoS
Effective Semantic Web Service Composition Framework Based on QoSsethuraman R
 
3.9 external sorting
3.9 external sorting3.9 external sorting
3.9 external sortingKrish_ver2
 
Graph theory
Graph theoryGraph theory
Graph theoryKumar
 

Andere mochten auch (20)

07. disjoint set
07. disjoint set07. disjoint set
07. disjoint set
 
Sets and disjoint sets union123
Sets and disjoint sets union123Sets and disjoint sets union123
Sets and disjoint sets union123
 
Advanced Algorithms #1 - Union/Find on Disjoint-set Data Structures.
Advanced Algorithms #1 - Union/Find on Disjoint-set Data Structures.Advanced Algorithms #1 - Union/Find on Disjoint-set Data Structures.
Advanced Algorithms #1 - Union/Find on Disjoint-set Data Structures.
 
Set data structure
Set data structure Set data structure
Set data structure
 
Set Operations - Union Find and Bloom Filters
Set Operations - Union Find and Bloom FiltersSet Operations - Union Find and Bloom Filters
Set Operations - Union Find and Bloom Filters
 
Union find
Union findUnion find
Union find
 
Time complexity of union find
Time complexity of union findTime complexity of union find
Time complexity of union find
 
Algorithms, Union Find
Algorithms, Union FindAlgorithms, Union Find
Algorithms, Union Find
 
17 Disjoint Set Representation
17 Disjoint Set Representation17 Disjoint Set Representation
17 Disjoint Set Representation
 
chapter24.ppt
chapter24.pptchapter24.ppt
chapter24.ppt
 
Agile Project Management (Workshop)
Agile Project Management (Workshop)Agile Project Management (Workshop)
Agile Project Management (Workshop)
 
18 Basic Graph Algorithms
18 Basic Graph Algorithms18 Basic Graph Algorithms
18 Basic Graph Algorithms
 
lecture 21
lecture 21lecture 21
lecture 21
 
Huffman tree
Huffman tree Huffman tree
Huffman tree
 
Set data structure 2
Set data structure 2Set data structure 2
Set data structure 2
 
Effective Semantic Web Service Composition Framework Based on QoS
Effective Semantic Web Service Composition Framework Based on QoSEffective Semantic Web Service Composition Framework Based on QoS
Effective Semantic Web Service Composition Framework Based on QoS
 
3.9 external sorting
3.9 external sorting3.9 external sorting
3.9 external sorting
 
Graph theory
Graph theoryGraph theory
Graph theory
 
Set concepts
Set conceptsSet concepts
Set concepts
 
Graph theory
Graph theoryGraph theory
Graph theory
 

Ähnlich wie Disjoint Sets Data Structure (Chap. 21

Introduction to Neural Networks and Deep Learning from Scratch
Introduction to Neural Networks and Deep Learning from ScratchIntroduction to Neural Networks and Deep Learning from Scratch
Introduction to Neural Networks and Deep Learning from ScratchAhmed BESBES
 
Open GL 04 linealgos
Open GL 04 linealgosOpen GL 04 linealgos
Open GL 04 linealgosRoziq Bahtiar
 
Integration
IntegrationIntegration
IntegrationRipaBiba
 
Litvinenko_RWTH_UQ_Seminar_talk.pdf
Litvinenko_RWTH_UQ_Seminar_talk.pdfLitvinenko_RWTH_UQ_Seminar_talk.pdf
Litvinenko_RWTH_UQ_Seminar_talk.pdfAlexander Litvinenko
 
GradStudentSeminarSept30
GradStudentSeminarSept30GradStudentSeminarSept30
GradStudentSeminarSept30Ryan White
 
Functions for Grade 10
Functions for Grade 10Functions for Grade 10
Functions for Grade 10Boipelo Radebe
 
On Spaces of Entire Functions Having Slow Growth Represented By Dirichlet Series
On Spaces of Entire Functions Having Slow Growth Represented By Dirichlet SeriesOn Spaces of Entire Functions Having Slow Growth Represented By Dirichlet Series
On Spaces of Entire Functions Having Slow Growth Represented By Dirichlet SeriesIOSR Journals
 
On the Seidel’s Method, a Stronger Contraction Fixed Point Iterative Method o...
On the Seidel’s Method, a Stronger Contraction Fixed Point Iterative Method o...On the Seidel’s Method, a Stronger Contraction Fixed Point Iterative Method o...
On the Seidel’s Method, a Stronger Contraction Fixed Point Iterative Method o...BRNSS Publication Hub
 
Z transform
Z transformZ transform
Z transformnirav34
 
Mathsclass xii (exampler problems)
Mathsclass xii (exampler problems)Mathsclass xii (exampler problems)
Mathsclass xii (exampler problems)nitishguptamaps
 
The multilayer perceptron
The multilayer perceptronThe multilayer perceptron
The multilayer perceptronESCOM
 
Radial Basis Function Interpolation
Radial Basis Function InterpolationRadial Basis Function Interpolation
Radial Basis Function InterpolationJesse Bettencourt
 

Ähnlich wie Disjoint Sets Data Structure (Chap. 21 (20)

Introduction to Neural Networks and Deep Learning from Scratch
Introduction to Neural Networks and Deep Learning from ScratchIntroduction to Neural Networks and Deep Learning from Scratch
Introduction to Neural Networks and Deep Learning from Scratch
 
Soft Heaps
Soft HeapsSoft Heaps
Soft Heaps
 
SlidesL28.pdf
SlidesL28.pdfSlidesL28.pdf
SlidesL28.pdf
 
Open GL 04 linealgos
Open GL 04 linealgosOpen GL 04 linealgos
Open GL 04 linealgos
 
Cse41
Cse41Cse41
Cse41
 
Integration
IntegrationIntegration
Integration
 
2018 MUMS Fall Course - Statistical Representation of Model Input (EDITED) - ...
2018 MUMS Fall Course - Statistical Representation of Model Input (EDITED) - ...2018 MUMS Fall Course - Statistical Representation of Model Input (EDITED) - ...
2018 MUMS Fall Course - Statistical Representation of Model Input (EDITED) - ...
 
It 05104 digsig_1
It 05104 digsig_1It 05104 digsig_1
It 05104 digsig_1
 
Litvinenko_RWTH_UQ_Seminar_talk.pdf
Litvinenko_RWTH_UQ_Seminar_talk.pdfLitvinenko_RWTH_UQ_Seminar_talk.pdf
Litvinenko_RWTH_UQ_Seminar_talk.pdf
 
Daa chapter7
Daa chapter7Daa chapter7
Daa chapter7
 
GradStudentSeminarSept30
GradStudentSeminarSept30GradStudentSeminarSept30
GradStudentSeminarSept30
 
Functions for Grade 10
Functions for Grade 10Functions for Grade 10
Functions for Grade 10
 
On Spaces of Entire Functions Having Slow Growth Represented By Dirichlet Series
On Spaces of Entire Functions Having Slow Growth Represented By Dirichlet SeriesOn Spaces of Entire Functions Having Slow Growth Represented By Dirichlet Series
On Spaces of Entire Functions Having Slow Growth Represented By Dirichlet Series
 
On the Seidel’s Method, a Stronger Contraction Fixed Point Iterative Method o...
On the Seidel’s Method, a Stronger Contraction Fixed Point Iterative Method o...On the Seidel’s Method, a Stronger Contraction Fixed Point Iterative Method o...
On the Seidel’s Method, a Stronger Contraction Fixed Point Iterative Method o...
 
Z transform
Z transformZ transform
Z transform
 
Mathsclass xii (exampler problems)
Mathsclass xii (exampler problems)Mathsclass xii (exampler problems)
Mathsclass xii (exampler problems)
 
The multilayer perceptron
The multilayer perceptronThe multilayer perceptron
The multilayer perceptron
 
03_AJMS_166_18_RA.pdf
03_AJMS_166_18_RA.pdf03_AJMS_166_18_RA.pdf
03_AJMS_166_18_RA.pdf
 
03_AJMS_166_18_RA.pdf
03_AJMS_166_18_RA.pdf03_AJMS_166_18_RA.pdf
03_AJMS_166_18_RA.pdf
 
Radial Basis Function Interpolation
Radial Basis Function InterpolationRadial Basis Function Interpolation
Radial Basis Function Interpolation
 

Mehr von Core Condor

Mehr von Core Condor (6)

Weighted graphs
Weighted graphsWeighted graphs
Weighted graphs
 
Red black 2
Red black 2Red black 2
Red black 2
 
Red black 1
Red black 1Red black 1
Red black 1
 
Graph isomorphism
Graph isomorphismGraph isomorphism
Graph isomorphism
 
Red blacktrees
Red blacktreesRed blacktrees
Red blacktrees
 
2 3 tree
2 3 tree2 3 tree
2 3 tree
 

Kürzlich hochgeladen

ISYU TUNGKOL SA SEKSWLADIDA (ISSUE ABOUT SEXUALITY
ISYU TUNGKOL SA SEKSWLADIDA (ISSUE ABOUT SEXUALITYISYU TUNGKOL SA SEKSWLADIDA (ISSUE ABOUT SEXUALITY
ISYU TUNGKOL SA SEKSWLADIDA (ISSUE ABOUT SEXUALITYKayeClaireEstoconing
 
AMERICAN LANGUAGE HUB_Level2_Student'sBook_Answerkey.pdf
AMERICAN LANGUAGE HUB_Level2_Student'sBook_Answerkey.pdfAMERICAN LANGUAGE HUB_Level2_Student'sBook_Answerkey.pdf
AMERICAN LANGUAGE HUB_Level2_Student'sBook_Answerkey.pdfphamnguyenenglishnb
 
Global Lehigh Strategic Initiatives (without descriptions)
Global Lehigh Strategic Initiatives (without descriptions)Global Lehigh Strategic Initiatives (without descriptions)
Global Lehigh Strategic Initiatives (without descriptions)cama23
 
Procuring digital preservation CAN be quick and painless with our new dynamic...
Procuring digital preservation CAN be quick and painless with our new dynamic...Procuring digital preservation CAN be quick and painless with our new dynamic...
Procuring digital preservation CAN be quick and painless with our new dynamic...Jisc
 
How to do quick user assign in kanban in Odoo 17 ERP
How to do quick user assign in kanban in Odoo 17 ERPHow to do quick user assign in kanban in Odoo 17 ERP
How to do quick user assign in kanban in Odoo 17 ERPCeline George
 
How to Add Barcode on PDF Report in Odoo 17
How to Add Barcode on PDF Report in Odoo 17How to Add Barcode on PDF Report in Odoo 17
How to Add Barcode on PDF Report in Odoo 17Celine George
 
Grade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdf
Grade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdfGrade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdf
Grade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdfJemuel Francisco
 
Karra SKD Conference Presentation Revised.pptx
Karra SKD Conference Presentation Revised.pptxKarra SKD Conference Presentation Revised.pptx
Karra SKD Conference Presentation Revised.pptxAshokKarra1
 
Proudly South Africa powerpoint Thorisha.pptx
Proudly South Africa powerpoint Thorisha.pptxProudly South Africa powerpoint Thorisha.pptx
Proudly South Africa powerpoint Thorisha.pptxthorishapillay1
 
HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...
HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...
HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...Nguyen Thanh Tu Collection
 
AUDIENCE THEORY -CULTIVATION THEORY - GERBNER.pptx
AUDIENCE THEORY -CULTIVATION THEORY -  GERBNER.pptxAUDIENCE THEORY -CULTIVATION THEORY -  GERBNER.pptx
AUDIENCE THEORY -CULTIVATION THEORY - GERBNER.pptxiammrhaywood
 
FILIPINO PSYCHology sikolohiyang pilipino
FILIPINO PSYCHology sikolohiyang pilipinoFILIPINO PSYCHology sikolohiyang pilipino
FILIPINO PSYCHology sikolohiyang pilipinojohnmickonozaleda
 
GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTS
GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTSGRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTS
GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTSJoshuaGantuangco2
 
ENGLISH 7_Q4_LESSON 2_ Employing a Variety of Strategies for Effective Interp...
ENGLISH 7_Q4_LESSON 2_ Employing a Variety of Strategies for Effective Interp...ENGLISH 7_Q4_LESSON 2_ Employing a Variety of Strategies for Effective Interp...
ENGLISH 7_Q4_LESSON 2_ Employing a Variety of Strategies for Effective Interp...JhezDiaz1
 
Transaction Management in Database Management System
Transaction Management in Database Management SystemTransaction Management in Database Management System
Transaction Management in Database Management SystemChristalin Nelson
 
Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17Celine George
 
Inclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdf
Inclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdfInclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdf
Inclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdfTechSoup
 
MULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptx
MULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptxMULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptx
MULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptxAnupkumar Sharma
 

Kürzlich hochgeladen (20)

ISYU TUNGKOL SA SEKSWLADIDA (ISSUE ABOUT SEXUALITY
ISYU TUNGKOL SA SEKSWLADIDA (ISSUE ABOUT SEXUALITYISYU TUNGKOL SA SEKSWLADIDA (ISSUE ABOUT SEXUALITY
ISYU TUNGKOL SA SEKSWLADIDA (ISSUE ABOUT SEXUALITY
 
AMERICAN LANGUAGE HUB_Level2_Student'sBook_Answerkey.pdf
AMERICAN LANGUAGE HUB_Level2_Student'sBook_Answerkey.pdfAMERICAN LANGUAGE HUB_Level2_Student'sBook_Answerkey.pdf
AMERICAN LANGUAGE HUB_Level2_Student'sBook_Answerkey.pdf
 
Global Lehigh Strategic Initiatives (without descriptions)
Global Lehigh Strategic Initiatives (without descriptions)Global Lehigh Strategic Initiatives (without descriptions)
Global Lehigh Strategic Initiatives (without descriptions)
 
FINALS_OF_LEFT_ON_C'N_EL_DORADO_2024.pptx
FINALS_OF_LEFT_ON_C'N_EL_DORADO_2024.pptxFINALS_OF_LEFT_ON_C'N_EL_DORADO_2024.pptx
FINALS_OF_LEFT_ON_C'N_EL_DORADO_2024.pptx
 
Procuring digital preservation CAN be quick and painless with our new dynamic...
Procuring digital preservation CAN be quick and painless with our new dynamic...Procuring digital preservation CAN be quick and painless with our new dynamic...
Procuring digital preservation CAN be quick and painless with our new dynamic...
 
How to do quick user assign in kanban in Odoo 17 ERP
How to do quick user assign in kanban in Odoo 17 ERPHow to do quick user assign in kanban in Odoo 17 ERP
How to do quick user assign in kanban in Odoo 17 ERP
 
How to Add Barcode on PDF Report in Odoo 17
How to Add Barcode on PDF Report in Odoo 17How to Add Barcode on PDF Report in Odoo 17
How to Add Barcode on PDF Report in Odoo 17
 
Grade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdf
Grade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdfGrade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdf
Grade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdf
 
Karra SKD Conference Presentation Revised.pptx
Karra SKD Conference Presentation Revised.pptxKarra SKD Conference Presentation Revised.pptx
Karra SKD Conference Presentation Revised.pptx
 
Proudly South Africa powerpoint Thorisha.pptx
Proudly South Africa powerpoint Thorisha.pptxProudly South Africa powerpoint Thorisha.pptx
Proudly South Africa powerpoint Thorisha.pptx
 
HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...
HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...
HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...
 
LEFT_ON_C'N_ PRELIMS_EL_DORADO_2024.pptx
LEFT_ON_C'N_ PRELIMS_EL_DORADO_2024.pptxLEFT_ON_C'N_ PRELIMS_EL_DORADO_2024.pptx
LEFT_ON_C'N_ PRELIMS_EL_DORADO_2024.pptx
 
AUDIENCE THEORY -CULTIVATION THEORY - GERBNER.pptx
AUDIENCE THEORY -CULTIVATION THEORY -  GERBNER.pptxAUDIENCE THEORY -CULTIVATION THEORY -  GERBNER.pptx
AUDIENCE THEORY -CULTIVATION THEORY - GERBNER.pptx
 
FILIPINO PSYCHology sikolohiyang pilipino
FILIPINO PSYCHology sikolohiyang pilipinoFILIPINO PSYCHology sikolohiyang pilipino
FILIPINO PSYCHology sikolohiyang pilipino
 
GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTS
GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTSGRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTS
GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTS
 
ENGLISH 7_Q4_LESSON 2_ Employing a Variety of Strategies for Effective Interp...
ENGLISH 7_Q4_LESSON 2_ Employing a Variety of Strategies for Effective Interp...ENGLISH 7_Q4_LESSON 2_ Employing a Variety of Strategies for Effective Interp...
ENGLISH 7_Q4_LESSON 2_ Employing a Variety of Strategies for Effective Interp...
 
Transaction Management in Database Management System
Transaction Management in Database Management SystemTransaction Management in Database Management System
Transaction Management in Database Management System
 
Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17
 
Inclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdf
Inclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdfInclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdf
Inclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdf
 
MULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptx
MULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptxMULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptx
MULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptx
 

Disjoint Sets Data Structure (Chap. 21

  • 1.
  • 2.
  • 3.
  • 4.
  • 5. Linked-lists for two sets head tail g head tail c head Set { c , h , e } Set { f , g } UNION of two Sets e tail c h e f f g h
  • 6.
  • 7.
  • 8.
  • 9.
  • 10.
  • 11. Path Compression f e d c f e d c
  • 12.
  • 13.
  • 14.
  • 15.
  • 16.
  • 17.
  • 18.
  • 19.
  • 20.
  • 21.
  • 22.
  • 23.
  • 24.
  • 25.
  • 26.
  • 27.
  • 28.
  • 29.
  • 30.
  • 31.
  • 32.