Relational Data Clustering
Models, Algorithms, and Applications
Seiten
2010
Chapman & Hall/CRC (Verlag)
978-1-4200-7261-7 (ISBN)
Chapman & Hall/CRC (Verlag)
978-1-4200-7261-7 (ISBN)
Presents a comprehensive overview of relational data clustering in data mining research. This book reflects the emergence of relational data clustering as an important field of data clustering, with applications in text mining, social network analysis, collaborative filtering, and bioinformatics.
A culmination of the authors’ 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.
A culmination of the authors’ 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.
Bo Long is a scientist at Yahoo! Labs in Sunnyvale, California. Zhongfei Zhang is an associate professor in the computer science department at the State University of New York in Binghamton. Philip S. Yu is a professor in the computer science department and the Wexler Chair in Information Technology at the University of Illinois in Chicago.
Introduction. Models. Algorithms. Applications. Summary. References. Index.
| Erscheint lt. Verlag | 26.5.2010 |
|---|---|
| Zusatzinfo | 25 Tables, black and white; 30 Illustrations, black and white |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Gewicht | 560 g |
| Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
| Mathematik / Informatik ► Mathematik ► Computerprogramme / Computeralgebra | |
| ISBN-10 | 1-4200-7261-7 / 1420072617 |
| ISBN-13 | 978-1-4200-7261-7 / 9781420072617 |
| Zustand | Neuware |
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