2nd CALL FOR CHAPTER PROPOSALS:
Proposal Submission Deadline: April 30, 2013
Biologically-Inspired Techniques for Knowledge Discovery and Data Mining
Advances in Data Mining and Database Management (ADMDM) Book Series
A book edited by Dr. Shafiq Alam, Dr. Yun Sing Koh, and Prof. Gillian Dobbie
University of Auckland, New Zealand
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Introduction
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Biological inspired data mining techniques have been intensively used in different data mining applications such as data clustering, classification, association rule mining, sequential pattern mining, outlier detection, feature selection and information extraction in many application areas, such as healthcare and bioinformatics. The techniques include Neural Networks, Fuzzy Systems, Genetic Algorithms, Ant Colony Optimization, Particle Swarm Optimization, Artificial Immune Systems, Culture Algorithms, Social evolution, and Artificial Bee Colony Optimization. A huge increase in the number of papers and citations in the area has been observed in the past decade, which is clear evidence of the popularity of these techniques.
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Objective of the Book
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The aim of this book is to highlight the contemporary research in the area of Biologically-Inspired techniques in different data mining domains, and the implementation of these techniques in real life data mining problems. The book will publish some of the state of the art work in this area and share the good practices that have enabled this area grow and flourish. The book will also contribute to extending the knowledge by providing quality work from established researchers that can be used by new researchers in the area.
The book calls for high quality chapters outlining current research, literature surveys, theoretical and empirical studies, and other relevant work including but not limited to the following areas:
1. Particle Swarm Optimization (PSO)
- PSO based clustering
- PSO based classification
- PSO based outlier detection
- PSO based feature selection
2. Ant Colony Optimization (ACO)
- ACO based clustering
- ACO based classification
- ACO based feature selection
- ACO based association rules mining
- ACO based sequential patterns mining
3. Artificial Immune Systems (AIS)
- Intrusion detection using AIS
- Clustering using AIS
- Decision support system using AIS
4. Bee Colony Optimization (BCO)
- BCO for pattern matching
- Clustering using BCO
5. Artificial Neural Networks (ANN)
- ANN based pattern matching and discover
- Classification rules discovery using ANN
- Forecasting using ANN
6. Genetic Algorithms (GA’s)
- Clustering, classification and parameter tuning using GA’s
- GA’s based feature extraction and selection
7. Fuzzy systems (FS)
- Fuzzy clustering
- Fuzzy classification
- Fuzzy Association rules discovery
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Target Audience
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The primary target of this book is the research community in the area of computational intelligence, machine learning, and data mining. However, the book is equally of interest for other KDD areas such as data analysis and preprocessing, big data management, web mining, optimization based data mining, and recommender systems. Specifically, it will be very useful for researchers from computational intelligence and evolutionary computation to update their knowledge about different application areas of their research, experimentation, and evaluation methods in the area of KDD.
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Submission Procedure
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Researchers and practitioners are invited to submit on or before April 30, 2013, a 2-3 page chapter proposal clearly explaining the mission and concerns of his or her proposed chapter. Authors of accepted proposals will be notified by May 15, 2013 about the status of their proposals and sent chapter guidelines. Full chapters are expected to be submitted by August 30, 2013. All submitted chapters will be reviewed on a double-blind review basis. Contributors may also be requested to serve as reviewers for this project.
Publisher
This book is scheduled to be published by IGI Global (formerly Idea Group Inc.), publisher of the “Information Science Reference” (formerly Idea Group Reference), “Medical Information Science Reference,” “Business Science Reference,” and “Engineering Science Reference” imprints. For additional information regarding the publisher, please visit
www.igi-global.com. This publication is anticipated to be released in 2014.
Important Dates
April 30, 2013: Proposal Submission Deadline
May 15, 2013: Notification of Acceptance
August 30, 2013: Full Chapter Submission
October 30, 2013: Review Results Returned
November 30, 2013: Final Chapter Submission
February 15, 2014: Final Deadline
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Inquiries and submissions can be forwarded electronically (Word document) or by mail to:
Dr. Shafiq Alam
Department of Computer Science
UNIVERSITY OF AUCKLAND
Tel.: +6493737599 ext. 82128 • Fax: +6493737453
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Kind Regards,
Shafiq Alam
Postdoctoral Research Fellow,
Department of Computer Science,
University of Auckland, New Zealand.