Relational Data Clustering
- Models, Algorithms, and Applications
- Indbinding:
- Paperback
- Sideantal:
- 216
- Udgivet:
- 19. september 2019
- Størrelse:
- 156x234x0 mm.
- Vægt:
- 453 g.
- 8-11 hverdage.
- 13. december 2024
Forlænget returret til d. 31. januar 2025
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- 20 timers lytning og læsning
- Adgang til 70.000+ titler
- Ingen binding
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Ingen binding og kan opsiges når som helst.
- 1 valgfrit digitalt ugeblad
- 20 timers lytning og læsning
- Adgang til 70.000+ titler
- Ingen binding
Abonnementet koster 75 kr./md.
Ingen binding og kan opsiges når som helst.
Beskrivelse af Relational Data Clustering
A culmination of the authorsΓÇÖ years of extensive research on this topic, Relational Data Clustering: Models, Algorithms, and Applications addresses the fundamentals and applications of relational data clustering. It describes theoretic models and algorithms and, through examples, shows how to apply these models and algorithms to solve real-world problems.
After defining the field, the book introduces different types of model formulations for relational data clustering, presents various algorithms for the corresponding models, and demonstrates applications of the models and algorithms through extensive experimental results. The authors cover six topics of relational data clustering:
Clustering on bi-type heterogeneous relational data
Multi-type heterogeneous relational data
Homogeneous relational data clustering
Clustering on the most general case of relational data
Individual relational clustering framework
Recent research on evolutionary clustering
This book focuses on both practical algorithm derivation and theoretical framework construction for relational data clustering. It provides a complete, self-contained introduction to advances in the field.
After defining the field, the book introduces different types of model formulations for relational data clustering, presents various algorithms for the corresponding models, and demonstrates applications of the models and algorithms through extensive experimental results. The authors cover six topics of relational data clustering:
Clustering on bi-type heterogeneous relational data
Multi-type heterogeneous relational data
Homogeneous relational data clustering
Clustering on the most general case of relational data
Individual relational clustering framework
Recent research on evolutionary clustering
This book focuses on both practical algorithm derivation and theoretical framework construction for relational data clustering. It provides a complete, self-contained introduction to advances in the field.
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