Advances in Fuzzy Clustering and its Applications

- List of Contributors.

- Foreword.

- Preface.

Part I Fundamentals.
1 Fundamentals of Fuzzy Clustering (Rudolf Kruse, Christian Ding and Marie-Jeanne Lesot).
2 Relational Fuzzy Clustering (Thomas A. Runkler).
3 Fuzzy Clustering with Minkowski Distance Functions (Patrick J.F. Groenen, Uzay Kaymak and Joost van Rosmalen).
4 Soft Cluster Ensembles (Kunal Punera and Joydeep Ghosh).

Part II Visualization.
5 Aggregation and Visualization of Fuzzy Clusters Based on Fuzzy Similarity Measures (Jos Abonyi and Bals Feil).
6 Interactive Exploration of Fuzzy Clusters (Bernd Wiswedel, David E. Patterson and Michael R. Berthold).

Part III Algorithms and Computational Aspects.
7 Fuzzy Clustering with Participatory Learning and Applications (Leila Roling Scariot da Silva, Fernando Gomide and Ronald Yager).
8 Fuzzy Clustering of Fuzzy Data (Pierpaolo D'Urso).
9 Inclusion-based Fuzzy Clustering (Samia Nefti-Meziani and Mourad Oussalah).
10 Mining Diagnostic Rules Using Fuzzy Clustering (Giovanna Castellano, Anna M. Fanelli and Corrado Mencar).
11 Fuzzy Regression Clustering (Mikal Sato-Ilic).
12 Implementing Hierarchical Fuzzy Clustering in Fuzzy Modeling Using the Weighted Fuzzy C-means (George E. Tsekouras).
13 Fuzzy Clustering Based on Dissimilarity Relations Extracted from Data (Mario G.C.A. Cimino, Beatrice Lazzerini and Francesco Marcelloni).
14 Simultaneous Clustering and Feature Discrimination with Applications (Hichem Frigui).

Part IV Real-time and Dynamic Clustering.
15 Fuzzy Clustering in Dynamic Data Mining - Techniques and Applications (Richard Weber).
16 Fuzzy Clustering of Parallel Data Streams (Jgen Beringer and Eyke Hlermeier).
17 Algorithms for Real-time Clustering and Generation of Rules from Data (Dimitar Filev and Plamer Angelov).

Part V Applications and Case Studies.
18 Robust Exploratory Analysis of Magnetic Resonance Images using FCM with Feature Partitions (Mark D. Alexiuk and Nick J. Pizzi).
19 Concept Induction via

JosValente de Oliveira received his Ph.D. (1996), M.Sc. (1992), and the "Licenciado" degree in Electrical and Computer Engineering from the IST, Technical University of Lisbon. Currently he is an Assistant Professor in the Faculty of Science and Technology at the University of Algarve where he served as Deputy Dean from 2002-2003. He was recently appointed director of the University of Algarve Informatics Lab, a research laboratory specializing in computational intelligence including fuzzy sets, fuzzy and intelligent systems, machine learning, and optimization.

Witold Pedrycz is a Professor and Canada Research Chair (CRC) in the Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada. He is also with the Systems Research Institute of the Polish Academy of Sciences. He is actively pursuing research in computational intelligence, fuzzy modeling, knowledge discovery and data mining, fuzzy control including fuzzy controllers, pattern recognition, knowledge-based neural networks, relational computation, bioinformatics, and Software Engineering. He currently serves as an Associate Editor of IEEE Transactions on Fuzzy Systems.

Researchers, as well as those with incipient interest in the field, will find this book very useful and informative. ( Computing Reviews , July 8, 2008)