- From: Yanchang Zhao <yczhao@it.uts.edu.au>
- Date: Sun, 20 May 2007 22:54:41 +1000
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Deadline extended to 31 May: KDD'07 Workshop on Domain Driven Data Mining ******************************************************************** Call for Papers 2007 ACM SIGKDD Workshop on Domain Driven Data Mining (DDDM 2007) San Jose, California, USA, 12th August 2007 In conjunction with ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'07) URL: http://datamining.it.uts.edu.au/dddm/ ******************************************************************** The "2007 ACM SIGKDD Workshop on Domain Driven Data Mining (DDDM2007)" aims to provide a premier forum for sharing findings, knowledge, insight, experience and lessons in tackling potential challenges in discovering actionable knowledge from complex domain problems, promoting interaction and filling the gap between academia and business, and driving a paradigm shift from interesting hidden pattern mining to actionable knowledge discovery in varying data mining domains. The workshop welcomes theoretical and applied disseminations that make efforts (1) to expose next-generation data mining methodology for actionable knowledge discovery, identifying how KDD techniques can better contribute to critical domain problems in theory and practice; (2) to uncover domain-driven data mining techniques identifying how KDD can better strengthen business intelligence in complex enterprise applications; (3) to disclose the applications of domain-driven data mining identifying how KDD can be effectively deployed into solving complex practical problems; and (4) to identify challenges and directions for future research and development in the dialogue between academia and business. Topics ------ The SIGKDD DDDM2007 Workshop solicits original theoretical and practical research on topics including, but not limited to, the following aspects: * Domain-driven data mining methodology and project management * Domain-driven KDD infrastructure and system support * Knowledge actionability and actionable knowledge discovery framework * Involvement of human intelligence, domain intelligence, web intelligence * Mining in-depth patterns and deep data intelligence * Intelligence meta-synthesis in KDD * Human-centered mining and human-mining interaction * Activity, impact, event, process and workflow mining * Unbalanced, constraint, dynamic and stream mining * Reliability, trust, privacy, utility, issues in data mining * Enterprise-oriented, spatio-temporal, multiple source mining * Ontology and knowledge engineering and management * Computational performance and actionability enhancement * Domain specific mining such as security mining, bioinformatic mining, etc. Submission Instructions ----------------------- Interested authors should submit their papers as an email attachment to the Co-Chair (kdd at it.uts.edu.au) of the ACM SIGKDD Workshop on Domain Driven Data Mining (DDDM 2007). Submissions should be prepared using the standard ACM format (http://www.acm.org/sigs/pubs/proceed/template.html) in MS Word or PDF format. Manuscripts must not exceed 10 pages, and present a cover page which should include the paper title, author(s), authors' affiliations, e-mail addresses, contact numbers, postal address, and an abstract. Important dates --------------- Submission of Papers: Extended to 31 May Notification: June 20, 2007 Camera Ready: July 10, 2007 Half-day Workshop Presentation: August 12, 2007 Publication Plans ---------------------- The workshop proceedings will be published by Springer. Organizing Committee -------------------- General Chair Philips Yu, IBM T.J. Watson Research Center, USA Workshop Chairs Chengqi Zhang, University of Technology, Sydney, Australia Graham Williams, Australian Taxation Office, Australia Longbing Cao, University of Technology, Sydney, Australia Organizing Chair Yanchang Zhao, University of Technology, Sydney, Australia Webmaster Chao Luo, University of Technology, Sydney, Australia Contacts -------- For general questions: Longbing Cao (lbcao at it.uts.edu.au) For paper submission: Yanchang Zhao (yczhao at it.uts.edu.au) For website: Chao Luo (chaoluo at it.uts.edu.au)
Received on Sunday, 20 May 2007 12:55:14 UTC