Data mining for association rules and sequential patterns: sequential and parallel algorithms
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
New York u.a.
Springer
2001
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | X, 254 S. Ill., graph. Darst. |
| ISBN: | 0387950486 |
Internformat
MARC
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| 100 | 1 | |a Adamo, Jean-Marc |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Data mining for association rules and sequential patterns |b sequential and parallel algorithms |c Jean-Marc Adamo |
| 264 | 1 | |a New York u.a. |b Springer |c 2001 | |
| 300 | |a X, 254 S. |b Ill., graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 650 | 4 | |a Algorithmes | |
| 650 | 7 | |a Algoritmen |2 gtt | |
| 650 | 4 | |a Data Mining | |
| 650 | 7 | |a Data mining |2 gtt | |
| 650 | 7 | |a INTELIGÊNCIA ARTIFICIAL |2 larpcal | |
| 650 | 7 | |a MINERAÇÃO DE DADOS |2 larpcal | |
| 650 | 7 | |a Parallelprogrammering |2 gtt | |
| 650 | 7 | |a Sequentiële analyse (statistiek) |2 gtt | |
| 650 | 4 | |a Computer algorithms | |
| 650 | 4 | |a Data mining | |
| 650 | 0 | 7 | |a Data Mining |0 (DE-588)4428654-5 |2 gnd |9 rswk-swf |
| 689 | 0 | 0 | |a Data Mining |0 (DE-588)4428654-5 |D s |
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Datensatz im Suchindex
| _version_ | 1804128390631915520 |
|---|---|
| adam_text | Jean-Marc Adamo
Data Mining for
Association Rules
and Sequential Patterns
Sequential and Parallel Algorithms
With 54 Illustrations
Springer
Contents
Preface v
1 Introduction l
2 Search Space Partition-Based Rule Mining 5
2 1 Problem Statement 5
211 Canonical Attribute Sequences (cas) 5
212 Database 6
213 Support 7
214 Association Rule 7
215 Problem Statement 9
2 2 Search Space 9
2 3 Splitting Procedure 11
2 4 Enumerating o-Frequent Attribute Sets (cass) 13
2 5 Sequential Enumeration Procedure 17
2 6 Parallel Enumeration Procedure 19
261 Initial Load Balancing 19
262 Computing the Starting Sets 20
263 Enumeration Procedure 23
264 Dynamic Load Balancing 23
2 7 Generating the Association Rules 24
271 Sequential Generation 26
272 Parallel Generation 27
3 Apriori and Other Algorithms 33
3 1 Early Algorithms 33
311 AIS 33
312 SETM 33
3 2 The Apriori Algorithms 34
321 Apriori 34
322 AprioriTid 38
3 3 Direct Hashing and Pruning 41
331 Filtering Candidates 41
viii Contents
332 Database Trimming 42
333 The DHPAlgorithm 43
3 4 Dynamic Set Counting 46
4 Mining for Rules over Attribute Taxonomies 49
4 1 Association Rules over Taxonomies 50
4 2 Problem Statement and Algorithms 54
4 3 Pruning Uninteresting Rules 59
431 Measure of Interest 59
432 Rule Pruning Algorithm 61
433 Attribute Presence-Based Pruning 64
5 Constraint-Based Rule Mining 67
5 1 Boolean Constraints 67
511 Syntax 67
512 Semantics 68
513 Propagation of Boolean Constraints 70
5 2 Prime Implicants 70
5 3 Problem Statement and Algorithms 73
6 Data Partition-Based Rule Mining 79
6 1 Data Partitioning 79
611 Building a Probabilistic Model 80
612 Bounding Large Deviations for Onecas (Chernoff bounds) 81
613 Bounding Large Deviations for Sets ofcass 82
6 2 cas Enumeration with Partitioned Data 89
621 Data Partitioning 89
622 Local (^-Frequent cas Generation 89
623 Global a-Frequent cas Generation 90
7 Mining for Rules with Categorical and Metric Attributes 93
7 1 Interval Systems and Quantitative Rules 95
7 2 k-Partial Completeness 99
7 3 Pruning Uninteresting Rules 102
731 Measure of Interest 103
732 Attribute Presence-Based Pruning 108
7 4 Enumeration Algorithms 109
8 Optimizing Rules with Quantitative Attributes I l l
8 1 Solving 1-1-Type Rule Optimization Problems 113
811 Problem Statement 113
812 MOS Problem 114
813 MS CProblem 121
814 MG Problem 125
Data Mining for Association Rules and Sequential Patterns ix
8 2 Solving d-l-Type Rule Optimization Problems 125
8 3 Solving 1-q-Type Rule Optimization Problems 126
831 Problem Statement 126
832 MS CProblem 128
833 MG Problem 138
8 4 Solving d-q-Type Rule Optimization Problems 144
841 Problem Statement 144
842 Basic Enumeration 146
843 Enumeration with Pruning 147
844 Pruning the Instantiation Set 150
9 Beyond Support-Confidence Framework 151
91A Criticism of the Support-Confidence Framework 151
9 2 Conviction 153
9 3 Pruning Conviction-Based Rules 157
931 Analyzing Conviction 157
932 Transitivity-Based Pruning 158
933 Improvement-Based Pruning 158
9 4 One-Step Association Rule Mining 159
941 Building a Procedure for One-Step Mining 160
942 Building a Procedure for Improvement-Based Pruning 164
9 5 Correlated Attribute-Set Mining 167
951 Collective Strength 167
952 Correlated Attribute-Set Enumeration 172
9 6 Refining Conviction: Association Rule Intensity 178
961 Measure Construction 178
962 Properties 181
963 Relating a-int(s ^ u) to conv(s = u) 181
964 Mining with the Intensity Measure 182
965 a-Intensity Versus Intensity as Defined in [G96] 183
10 Search Space Partition-Based Sequential Pattern Mining 185
10 1 Problem Statement 185
10 1 1 Sequences ofcass 185
10 1 2 Database 186
10 1 3 Support 187
10 1 4 Problem Statement 189
10 2 Search Space 189
10 3 Splitting the Search Space 190
10 4 Splitting Procedure 195
10 5 Sequence Enumeration 200
10 5 1 Extending the Support Set Notion 201
10 5 2 Join Operations 202
10 5 3 Sequential Enumeration Procedure 208
10 5 4 Parallel Enumeration Procedure 215
x Contents
Appendix 1 Chernoff Bounds 229
Appendix 2 Partitioning in Figure 10 5: Beyond 3rd Power 233
Appendix 3 Partitioning in Figure 10 6: Beyond 3rd Power 237
References 245
Index 251
|
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| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.3 |
| dewey-search | 006.3 |
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| discipline | Informatik |
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| id | DE-604.BV013588477 |
| illustrated | Illustrated |
| indexdate | 2024-07-09T18:48:29Z |
| institution | BVB |
| isbn | 0387950486 |
| language | English |
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| spelling | Adamo, Jean-Marc Verfasser aut Data mining for association rules and sequential patterns sequential and parallel algorithms Jean-Marc Adamo New York u.a. Springer 2001 X, 254 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Algorithmes Algoritmen gtt Data Mining Data mining gtt INTELIGÊNCIA ARTIFICIAL larpcal MINERAÇÃO DE DADOS larpcal Parallelprogrammering gtt Sequentiële analyse (statistiek) gtt Computer algorithms Data mining Data Mining (DE-588)4428654-5 gnd rswk-swf Data Mining (DE-588)4428654-5 s DE-604 HEBIS Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009280436&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Adamo, Jean-Marc Data mining for association rules and sequential patterns sequential and parallel algorithms Algorithmes Algoritmen gtt Data Mining Data mining gtt INTELIGÊNCIA ARTIFICIAL larpcal MINERAÇÃO DE DADOS larpcal Parallelprogrammering gtt Sequentiële analyse (statistiek) gtt Computer algorithms Data mining Data Mining (DE-588)4428654-5 gnd |
| subject_GND | (DE-588)4428654-5 |
| title | Data mining for association rules and sequential patterns sequential and parallel algorithms |
| title_auth | Data mining for association rules and sequential patterns sequential and parallel algorithms |
| title_exact_search | Data mining for association rules and sequential patterns sequential and parallel algorithms |
| title_full | Data mining for association rules and sequential patterns sequential and parallel algorithms Jean-Marc Adamo |
| title_fullStr | Data mining for association rules and sequential patterns sequential and parallel algorithms Jean-Marc Adamo |
| title_full_unstemmed | Data mining for association rules and sequential patterns sequential and parallel algorithms Jean-Marc Adamo |
| title_short | Data mining for association rules and sequential patterns |
| title_sort | data mining for association rules and sequential patterns sequential and parallel algorithms |
| title_sub | sequential and parallel algorithms |
| topic | Algorithmes Algoritmen gtt Data Mining Data mining gtt INTELIGÊNCIA ARTIFICIAL larpcal MINERAÇÃO DE DADOS larpcal Parallelprogrammering gtt Sequentiële analyse (statistiek) gtt Computer algorithms Data mining Data Mining (DE-588)4428654-5 gnd |
| topic_facet | Algorithmes Algoritmen Data Mining Data mining INTELIGÊNCIA ARTIFICIAL MINERAÇÃO DE DADOS Parallelprogrammering Sequentiële analyse (statistiek) Computer algorithms |
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