CALL FOR CHAPTER
Proposal Submission Deadline: August 1, 2008
Intelligent Soft Computation and Evolving Data Mining:
Integrating Advanced Technology
Editors: Leon S.L. Wang, Tzung-Pei Hong
National University of Kaohsiung, Taiwan
Introduction
Since its inception, data mining has been described as "the nontrivial
extraction of implicit, previously unknown, and potentially useful
information from data." Data mining was usually used by business
intelligence organizations and analysts to extract useful information
from databases. But increasing applications of data mining have been
found in many other areas to extract information from the enormous
data sets generated by modern experimental and observational methods.
However, due to the intractable computational complexity of many
existing data mining techniques for real world problems, advanced
techniques that are tolerable to imprecision, uncertainty,
approximation, and adaptable to ever-changing environments are very
desirable.
In contrast to conventional hard computing, the basic ideas underlying
soft computing is to exploit the tolerance for imprecision,
uncertainty, partial truth, and approximation to achieve tractability,
robustness and low solution cost. At this juncture, the principal
constituents of soft computing are Fuzzy Logic (FL), Neural Computing
(NC), Evolutionary Computation (EC) Machine Learning (ML) and
Probabilistic Reasoning (PR), with the latter subsuming belief
networks, chaos theory and parts of learning theory. It has been
demonstrated in many areas that the soft computing methodologies are
complementary to many existing theories and technologies.
Objective of the Book
As a consequence, the main objective of this book is to provide an
international exchange for the synergy of new developments from two
different research disciplines. As such, through the fusion of diverse
techniques and applications, new and innovative ideas will be
stimulated. Moreover, the book will provide a highly regarded outlet
for the most emerging research in the fields and seeks to bridge
underrepresented themes within the data mining and soft computing
disciplines.
Recommended topics include, but are not limited to, the following:
Fuzz Sets Classification
Fuzzy Logic Clustering
Neural Networks Regression
Fuzzy-Neural Rule Generation
Genetic Algorithms Summarization
Machine Learning Dependency Modelling
Evolutionary Computation Association Rule
Probabilistic Reasoning Sequence Analysis
Belief Networks Web Intelligence
Chaos Theory Data Streams
Swamp Intelligence Text Mining
Self-adaptation Techniques Graph Mining
Learning Theory Social Network Analysis
Cooperative Learning Spatial Mining
Computational Intelligence Multi-relational Mining
Submission Procedure
Researchers and practitioners are invited to submit before August 1,
2008, 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 August 15, 2008 about the status of their
proposals and sent chapter guidelines. Full chapters are expected to
be submitted by October 31, 2008. All submitted chapters will be
reviewed on a double-blind review basis. This book is scheduled to be
published by IGI Global (formerly Idea Group Inc.), publisher of the
=93Information Science Reference=94 (formerly Idea Group Reference) and
=93Medical Information Science Reference=94 imprints. For additional
information regarding the publisher, please visit www.igi-global.com.
Im****tant Dates
August 1, 2008: First proposal deadline
August 15, 2008: Notification of acceptance
October 31, 2008: Full chapter deadline (Phase I)
December 20, 2008: Notification of acceptance (Phase I)
January 20, 2009: Revised chapter deadline (Phase II)
February 15, 2009: Notification of acceptance (Phase II)
March 15, 2009: Final accepted chapter deadline (Phase I & II)
Inquiries and submissions can be forwarded electronically (Word
do***ent) or by mail to:
Dr. Leon S.L. Wang1, Dr. T.P. Hong2
1Department of Information Management
2Department of Computer Science and Information Engineering
National University of Kaohsiung
Kaohsiung, TAIWAN 81148
Tel.: +886 7 591 9728 =95 Fax: +886 7 591 9328
E-mail: {slwang, tphong}@[EMAIL PROTECTED]
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