Data Mining and Knowledge Discovery Handbook

- New Added Topics: Graph Mining
- Sequence Mining
- Utility-Based Data Mining
- Swarm Intelligence.-Privacy Preserving DM
- Multimedia Data Mining
- Data Streaming Mining
- Data Mining in Bioinformatics
- Ontology Mining
- Reliability Issues of Knowledge Discovery
- Optimization-based Data Mining
- Distributed Data Mining
- Standards for Data Mining
- The Clementine Software
- The SAS Miner

All other topics updated to cover developments in the field:
- Introduction to knowledge discovery in databases
Part I Preprocessing methods
- Data cleansing
- Handling missing attribute values
- Geometric methods for feature extraction and dimensional reduction
- Dimension Reduction and feature selection
- Discretization methods
- outlier detection
Part II Supervised methods
- Introduction to supervised methods
- Decision trees
- Bayesian networks
- Data mining within a regression framework
- Support vector machines
Part III Unsupervised methods
- Clustering methods
- Association rules
- Frequent set mining
- Constraint-based data mining
- Link analysis
Part IV Soft computing methods
- Evolutionary algorithms for data mining
- Reinforcement-learning: an overview from a data mining perspective
- Neural networks
- Granular computing and rough sets
Part V Supporting methods
- Statistical methods for data mining
- Logics for data mining
- Wavelet methods in data mining
- Fractal mining
- Interestingness measures
- Quality assessment approaches in data mining
- Data mining model comparison
- Data mining query languages
Part VI Advanced methods
- Meta-learning
- Bias vs variance decomposition for regression and classification
- Mining with rare cases
- Mining data streams
- Mining high-dimensional data
- Text mining and information extraction
- Spatial data mining
- Data mining for imbalanced datasets: an overview
- Relational data mining
- Web mining
- A review of web document clustering approaches
- Causal discovery
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Prof. Oded Maimon is the Oracle chaired Professor at Tel-Aviv University, Previously at MIT. Oded is a leader expert in the field of data mining and knowledge discovery. He published many articles on new algorithms and seven significant award winning books in the field since 2000. He has also developed and implemented successful applications in the Industry. He heads an international research group sponsored by European Union awards.

Dr. Lior Rokach is a senior lecturer at the Department of Information System Engineering at Ben-Gurion University. He is a recognized expert in intelligent information systems and has held several leading positions in this field. His main areas of interest are Data Mining, Pattern Recognition, and Recommender Systems. Dr. Rokach is the author of over 70 refereed papers in leading journals, conference proceedings and book chapters. In addition he has authored six books and edited three others books.

From the reviews of the second edition:

"This handbook provides an excellent guide in every aspect of the discovery process. ... Contributors are drawn from noted academic institutions and companies around the world and across diverse disciplines. ... serves to define the current state of the art in knowledge discovery, and is particularly useful in cross-fertilization among a diverse set of application scenarios. It is an indispensable reference for researchers and an excellent starting point for advanced students taking graduate courses in this area. Summing Up: Highly recommended. Upper-division undergraduates through professionals/practitioners." (J. Y. Cheung, Choice, Vol. 48 (10), June, 2011)

"This edition treats new aspects (for instance, privacy) and new methods, like those based on swarm intelligence and multi-label classification. ... The book is a comprehensive and detailed reference. ... Each chapter contains a long list of references for further investigation. ... I recommend this comprehensive book to advanced readers--including designers and architects at software companies--interested in the R&D of data mining." (K. Balogh, ACM Computing Reviews, November, 2011)