Relational semi-supervised classification using multiple relations:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Abschlussarbeit Buch |
| Sprache: | English |
| Veröffentlicht: |
Aachen
Shaker
2011
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| Schriftenreihe: | Berichte aus der Informatik
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | X, 145 S. Ill., graph. Darst. 21 cm, 234 g |
| ISBN: | 9783844002010 |
Internformat
MARC
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Datensatz im Suchindex
| _version_ | 1804149066457677824 |
|---|---|
| adam_text | IMAGE 1
CONTENTS
1 INTRODUCTION 1
1.1 MOTIVATION 1
1.2 CONTRIBUTION 3
1.3 PUBLISHED WORK 4
1.4 CHAPTER OVERVIEW 5
2 PROBLEM DEFINITION 7
2.1 RELATIONS, GRAPHS, MATRICES AND KERNELS 7
2.1.1 RELATIONS 7
2.1.2 GRAPHS 8
2.1.3 MATRICES 9
2.1.4 KERNELS 10
2.2 ATTRIBUTE-BASED DATA 11
2.3 TIME SERIES DATA 12
2.4 RELATIONAL DATA 12
2.4.1 RELATIONAL ATTRIBUTES 14
2.4.2 RELATIONAL GRAPHS 15
2.4.3 SIMILARITY GRAPHS 16
2.4.4 MULTIPLE RELATIONS 16
2.5 SUPERVISED AND UNSUPERVISED CLASSIFICATION 18
2.5.1 SUPERVISED RELATIONAL CLASSIFICATION 18
2.6 SEMI-SUPERVISED CLASSIFICATION 19
2.6.1 SEMI-SUPERVISED RELATIONAL CLASSIFICATION 20
2.7 RELATIONAL CLASSIFICATION WITH MULTIPLE RELATIONS 21
3 STATE-OF-THE-ART METHODS AND RELATED WORK 23
3.1 RELATIONAL CLASSIFICATION METHODS 23
3.1.1 AGGREGATION-BASED CLASSIFIERS 23
3.1.2 RELATIONAL BAYESIAN CLASSIFIER 24
BIBLIOGRAFISCHE INFORMATIONEN HTTP://D-NB.INFO/1013759966
DIGITALISIERT DURCH
IMAGE 2
CONTENTS
3.1.3 RELATIONAL PROBABILITY TREES 25
3.1.4 LINK-BASED MULTINOMIAL NAIVE BAYES 26
3.1.5 LAZY LEARNER 26
3.1.6 PROBABILISTIC RELATIONAL MODELS 27
3.2 COLLECTIVE CLASSIFICATION ALGORITHMS 29
3.2.1 ITERATIVE CLASSIFICATION ALGORITHM 29
3.2.2 ITERATIVE INCREMENTAL ALGORITHM 30
3.2.3 RELAXATION LABELING 31
3.2.4 GIBBS SAMPLING 32
3.3 SUPERVISED RELATIONAL CLASSIFICATION 34
3.4 SEMI-SUPERVISED RELATIONAL CLASSIFICATION 35
3.5 CATEGORIZATION OF METHODS 36
3.6 SEMI-SUPERVISED GRAPH-BASED METHODS 38
3.6.1 REGULARIZATION METHODS 39
3.6.2 LABEL PROPAGATION METHODS 40
3.6.3 GRAPH KERNELS 42
3.7 RELATIONAL CLASSIFICATION USING MULTIPLE RELATIONS 45
SEMI-SUPERVISED MULTI-RELATIONAL CLASSIFICATION 51
4.1 RELATIONAL ENSEMBLE CLASSIFICATION 51
4.1.1 COLLECTIVE CLASSIFICATION ALGORITHM 52
4.1.2 RELATIONAL CLASSIFICATION ALGORITHM 52
4.1.2.1 RELATIONAL CLASSIFICATION IN SPARSE GRAPHS 54
4.1.2.2 ATTRIBUTE-BASED RELATIONAL METHODS 57
4.1.3 ENSEMBLE CLASSIFICATION ALGORITHM 57
4.2 RELATIONAL MULTI-KERNEL CLASSIFICATION 59
4.2.1 KERNELS 61
4.2.2 KERNEL WEIGHTS 61
4.2.3 KERNEL-BASED LEARNING ALGORITHMS 62
4.3 RELATIONAL MULTI-GRAPH CLASSIFICATION 63
4.4 EVALUATION 64
4.4.1 MULTI-CLASS AND MULTI-LABEL PROBLEM 65
4.4.2 EVALUATION MEASURES 65
4.4.3 DATASETS 66
4.4.4 EXPERIMENTS 68
4.4.4.1 INDIVIDUAL RELATIONS VS. MULTIPLE RELATIONS 68
4.4.4.2 COMPARISON OF DIFFERENT MULTI-RELATIONAL CLASSIFICATION
STRATEGIES 69
4.4.4.3 RELATIONAL ENSEMBLE CLASSIFICATION EXPERIMENTS . . .. 71
IMAGE 3
CONTENTS
4.4.4.4 ANALYSIS OF THE SPARSITY PROBLEM 79
4.4.4.5 COMBINING CONTENT AND RELATIONS 80
4.4.4.6 COMPARISON OF GRAPH KERNELS 81
RELATION EXTRACTION 84
5.1 RECORD LINKAGE RELATION EXTRACTION MODEL 84
5.2 EVALUATION 87
SEMI-SUPERVISED RELATIONAL TAG RECOMMENDATION 88
6.1 MOTIVATION 88
6.2 TAG RECOMMENDATIONS 90
6.2.1 GENERAL PROBLEM FORMULATION 90
6.2.2 NEW USER/RESOURCE PROBLEM 90
6.3 RELATED WORK 91
6.3.1 CONSTANT TAG RECOMMENDER MODELS 91
6.3.2 COLLABORATIVE FILTERING FOR TAG RECOMMENDATION 92 6.3.3 FOLKRANK
93
6.3.4 RANKING WITH TENSOR FACTORIZATION 94
6.3.5 PAIRWISE INTERACTION TENSOR FACTORIZATION 96
6.3.6 LATENT DIRICHLET ALLOCATION 97
6.4 SEMI-SUPERVISED MULTI-RELATIONAL TAG RECOMMENDATION 97 6.4.1
RELATIONS AND DATA REPRESENTATION IN SOCIAL TAGGING SYSTEMS . . 98 6.4.2
WEIGHTING SCHEMES 99
6.4.3 SEMI-SUPERVISED RELATIONAL TAG RECOMMENDATION METHODS . . . 100
6.4.4 NEW USER/RESOURCE PROBLEM 101
6.5 EVALUATION 103
6.5.1 DATASETS 103
6.5.2 EXPERIMENT SETTING 104
6.5.3 RESULTS AND DISCUSSION 106
SEMI-SUPERVISED RELATIONAL TIME SERIES CLASSIFICATION 110 7.1 MOTIVATION
110
7.2 STATE-OF-THE-ART MODELS AND RELATED WORK I LL
7.2.1 UNIVARIATE TIME SERIES CLASSIFICATION I LL
7.2.2 MULTIVARIATE T I ME SERIES CLASSIFICATION 112
7.2.3 SEMI-SUPERVISED T I ME SERIES CLASSIFICATION 114
7.3 UNIVARIATE SEMI-SUPERVISED RELATIONAL T I ME SERIES CLASSIFICATION .
. .. 114
7.4 MULTIVARIATE SEMI-SUPERVISED T I ME SERIES CLASSIFICATION 116
7.5 EVALUATION 116
IMAGE 4
CONTENTS
7.5.1 DATASETS 118
7.5.2 EXPERIMENTS 119
7.5.2.1 UNIVARIATE TIME SERIES CLASSIFICATION EXPERIMENT . . . 120
7.5.2.2 MULTIVARIATE TIME SERIES CLASSIFICATION EXPERIMENT . . 122
8 CONCLUSION 128
8.1 SUMMARY 128
8.2 OUTLOOK 130
INDEX 134
REFERENCES 145
|
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| author_facet | Preisach, Christine |
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| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.31 |
| dewey-search | 006.31 |
| dewey-sort | 16.31 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| format | Thesis Book |
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| spelling | Preisach, Christine Verfasser aut Relational semi-supervised classification using multiple relations Christine Preisach Aachen Shaker 2011 X, 145 S. Ill., graph. Darst. 21 cm, 234 g txt rdacontent n rdamedia nc rdacarrier Berichte aus der Informatik Zugl.: Hildesheim, Univ., Diss., 2010 Automatische Klassifikation (DE-588)4120957-6 gnd rswk-swf Wissensextraktion (DE-588)4546354-2 gnd rswk-swf Zeitreihe (DE-588)4127298-5 gnd rswk-swf Empfehlungssystem (DE-588)7511891-9 gnd rswk-swf Relationales Datenmodell (DE-588)4418263-6 gnd rswk-swf Teilüberwachtes Lernen (DE-588)4782452-9 gnd rswk-swf Social Tagging (DE-588)7629989-2 gnd rswk-swf (DE-588)4113937-9 Hochschulschrift gnd-content Automatische Klassifikation (DE-588)4120957-6 s Teilüberwachtes Lernen (DE-588)4782452-9 s Relationales Datenmodell (DE-588)4418263-6 s Wissensextraktion (DE-588)4546354-2 s Empfehlungssystem (DE-588)7511891-9 s Social Tagging (DE-588)7629989-2 s Zeitreihe (DE-588)4127298-5 s DE-604 DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=024967830&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Preisach, Christine Relational semi-supervised classification using multiple relations Automatische Klassifikation (DE-588)4120957-6 gnd Wissensextraktion (DE-588)4546354-2 gnd Zeitreihe (DE-588)4127298-5 gnd Empfehlungssystem (DE-588)7511891-9 gnd Relationales Datenmodell (DE-588)4418263-6 gnd Teilüberwachtes Lernen (DE-588)4782452-9 gnd Social Tagging (DE-588)7629989-2 gnd |
| subject_GND | (DE-588)4120957-6 (DE-588)4546354-2 (DE-588)4127298-5 (DE-588)7511891-9 (DE-588)4418263-6 (DE-588)4782452-9 (DE-588)7629989-2 (DE-588)4113937-9 |
| title | Relational semi-supervised classification using multiple relations |
| title_auth | Relational semi-supervised classification using multiple relations |
| title_exact_search | Relational semi-supervised classification using multiple relations |
| title_full | Relational semi-supervised classification using multiple relations Christine Preisach |
| title_fullStr | Relational semi-supervised classification using multiple relations Christine Preisach |
| title_full_unstemmed | Relational semi-supervised classification using multiple relations Christine Preisach |
| title_short | Relational semi-supervised classification using multiple relations |
| title_sort | relational semi supervised classification using multiple relations |
| topic | Automatische Klassifikation (DE-588)4120957-6 gnd Wissensextraktion (DE-588)4546354-2 gnd Zeitreihe (DE-588)4127298-5 gnd Empfehlungssystem (DE-588)7511891-9 gnd Relationales Datenmodell (DE-588)4418263-6 gnd Teilüberwachtes Lernen (DE-588)4782452-9 gnd Social Tagging (DE-588)7629989-2 gnd |
| topic_facet | Automatische Klassifikation Wissensextraktion Zeitreihe Empfehlungssystem Relationales Datenmodell Teilüberwachtes Lernen Social Tagging Hochschulschrift |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=024967830&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT preisachchristine relationalsemisupervisedclassificationusingmultiplerelations |