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AISB miscellaneous Bulletin Item

CF Chapters: Post-Mining of Association Rules

      Proposal Submission Deadline: January 31, 2008
           Full chapter submission: April 30, 2008

Post-Mining of Association Rules: Techniques for Effective
Knowledge Extraction

Dr.   Yanchang Zhao
Prof. Chengqi Zhang
Dr.   Longbing Cao

IGI Global (formerly Idea Group)

There are often a huge number of association rules
discovered in a data mining practice, making it difficult
for users to identify those that are of particular interest
to them. Therefore, it is important to remove insignificant
rules and prune redundancy as well as summarize, visualize
and post-mine the discovered rules. Moreover, the
information we can get from traditional association rules
is very limited, so new forms of association rules are
needed to discover useful and actionable knowledge. The
book aims to present a whole picture of the post-analysis,
summarization and new forms of association rules and
introduce the up-to-date research on the above topics to
extract useful knowledge from a large number of discovered
association rules.

The Overall Objective of the Book
The book will focus on the post-analysis of association
rules to extract useful and actionable knowledge from a
large number of discovered rules. It will cover interest,
redundancy, post-mining, summarization, presentation and
visualization of association rules, as well as novel forms
and new trends of association rules. It will not only
present academia with a systematic view of the current
research progress on the above topics, but it will also
help industry learn from the ideas and apply them to find
actionable knowledge in real-world applications.

The Target Audience
The audience of this book will be researchers in the field
of data mining, postgraduate students who are interested
in data mining, and industry data miners. Note that the
audience is not limited to those interested in association
rules because the post-mining of association rules involves
clustering, classification and many other techniques of
data mining, as well as statistics and artificial
intelligence, which are actually beyond association rule
mining itself.

Recommended topics include, but not limited to:
* Subjective & objective interestingness
* Removing redundancy in association rules
* Summarization and generalization of association rules
* Presentation and visualization of association rules
* Maintenance of association rules
* Post-mining of association rules, e.g., clustering
  association rules
* Class association rules and association classifier
* Quantitative association rules and inter-transaction
  association rules
* New forms/challenges/trends of association rules and
  association mining

Important Dates
2nd round proposal deadline:         January 31, 2008
Notification of proposal acceptance: February 28, 2008
Full chapter submission:             April 30, 2008
Notification of chapter review:      June 30, 2008
Revised chapter submission:          July 30, 2008
Final notification of acceptance:    August 15, 2008
Camera ready copy submission:        September 15, 2008

Submission Procedure
Researchers and practitioners are invited to submit on or
before January 31, 2008, a 2-5 page manuscript proposal
clearly explaining the mission and concerns of the proposed
chapter. Authors of accepted proposals will be notified by
February 28, 2008 about the status of their proposals and
sent chapter organizational guidelines. Full chapters are
expected to be submitted by April 30, 2008. All submitted
chapters will be reviewed on a double-blind review basis.
The book is scheduled to be published by IGI Global
(formerly Idea Group),, publisher of the
IGI Publishing (Idea Group Publishing), Information Science
Publishing, IRM Press, CyberTech Publishing, Information
Science Reference (formerly Idea Group Reference) and
Medical Information Science Reference imprints.

Detailed instructions are available at

Inquiries and submissions can be forwarded electronically
(Word document) to:

Dr. Yanchang Zhao
Faculty of Information Technology,
University of Technology, Sydney (UTS), Australia
Tel.: +61 2 6131 0264
Mobile: +61 4300 93392