1. DDDM 2008: The 2 nd International Workshop on Domain Driven Data Mining Philip S. Yu, Yanchang Zhao, Graham Williams, Carlos Soares

2. Data Sciences & Knowledge Discovery Research Lab 2 Outline DDDM: Domain Driven Data Mining DDDM 2007 DDDM 2008

3. Data Sciences & Knowledge Discovery Research Lab 3 Background In the last decade, data mining has emerged as one of most vivacious areas in information technology. Although many algorithms and techniques for data mining have been proposed, it still remains an open problem to successfully apply them to discover actionable knowledge in real-life applications in various domains.

4. Data Sciences & Knowledge Discovery Research Lab 4 DDDM The International Workshop on Domain Driven Data Mining (DDDM) 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, To promote the interaction of and bridge the gap between data mining research and business expectations, and To drive a paradigm shift from traditional data-centered hidden pattern mining to domain-driven actionable knowledge discovery.

5. Data Sciences & Knowledge Discovery Research Lab 5 Objectives To design next-generation data mining methodology for actionable knowledge discovery and identify how KDD techniques can better contribute to critical domain problems in theory and practice; To devise domain-driven data mining techniques to strengthen business intelligence in complex enterprise applications; To present the applications of domain-driven data mining and demonstrate how KDD can be effectively deployed to solve complex practical problems; and To identify challenges and future directions for data mining research and development in the dialogue between academia and industry.

6. Data Sciences & Knowledge Discovery Research Lab 6 DDDM 2007 San Jose, California, USA, on 12th August 2007 In conjunction with ACM SIGKDD'07 Website: http://datamining.it.uts.edu.au/dddm/ 8 papers accepted from 5 countries 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

7. Data Sciences & Knowledge Discovery Research Lab 7 DDDM 2008 Pisa, Italy, on December 15, 2008 In conjunction with IEEE ICDM'08 Website: http://datamining.it.uts.edu.au/dddm08/ http://datamining.it.uts.edu.au/dddm08/ 39 submissions from 12 countries (including papers forwarded from main conference) 10 papers accepted, with an acceptance rate of 26%

8. Data Sciences & Knowledge Discovery Research Lab 8 Organizing Committee General Chair Philip S. Yu University of Illinois at Chicago, USA Program Chairs Yanchang Zhao University of Technology, Sydney, Australia Graham Williams Australian Taxation Office, Australia Carlos Soares University of Porto, Portugal

9. Data Sciences & Knowledge Discovery Research Lab 9 Host Data Sciences & Knowledge Discovery Research Lab http://datamining.it.uts.edu.au Centre for Quantum Computation and Intelligent Systems http://www.qcis.uts.edu.au University of Technology, Sydney, Australia http://www.uts.edu.au

10. Data Sciences & Knowledge Discovery Research Lab 10 Program Committee Ronnie Alves Universidade do Minho, Portugal Elena Baralis Politecnico di Torino, Italy David Bell Queen's University Belfast, UK Petr Berka University of Economics of Prague, Czech Republic Jean-Francois Boulicaut INSA Lyon, France Longbing Cao University of Technology, Sydney, Australia Peter Christen The Australian National University, Australia Paulo Cortez University of Minho, Portugal Guozhu Dong Wright State University, USA Warwick Graco Australian Taxation Office, Australia Joshua Zhexue Huang The University of Hong Kong, Hong Kong Alexandros Kalousis The Universtity of Geneva, Switzerland Walter Kosters Leiden University, The Netherlands Christopher Leckie The University of Melbourne, Australia Chunhung Li Hong Kong Baptist University, Hong Kong Xue Li The University of Queensland, Australia Tsau Young Lin San Jose State University, USA

11. Data Sciences & Knowledge Discovery Research Lab 11 Program Committee (cont.) Donato Malerba University of Bari, Italy Engelbert Mephu Nguifo Universite d'Artois, France Ngoc Thanh Nguyen Wroclaw University of Technology, Poland Arlindo Oliveira IST/INESC-ID, Portugal Alexandre Plastino Universidade Federal Fluminense, Brazil Kulathur S. Rajasethupathy State University of New York, USA Yidong Shen Chinese Academy of Sciences, China Dan Simovici University of Massachusetts at Boston, USA Wei Wang Fudan University, China Jeffrey Xu Yu The Chinese University of Hong Kong, Hong Kong Carlo Zaniolo University of California, Los Angeles, USA Justin Zhan Carnegie Mellon University, USA Chengqi Zhang University of Technology, Sydney, Australia Huaifeng Zhang University of Technology, Sydney, Australia Mengjie Zhang Victoria University of Wellington, New Zealand Shichao Zhang Guangxi Normal University, China Zhi-Hua Zhou Nanjing University, China

12. Data Sciences & Knowledge Discovery Research Lab 12 TKDE Special Issue on DDDM IEEE Transactions on Knowledge and Data Engineering Special Issue on Domain Driven Data Mining Guest Editors: Chengqi Zhang, Philip S. Yu, David Bell Submission deadline: March 31, 2009 http://datamining.it.uts.edu.au/group/cfp/cfp- DDDM.doc http://datamining.it.uts.edu.au/group/cfp/cfp- DDDM.doc http://www.computer.org/portal/cms_docs_tran sactions/transactions/tkde/CFP/cfp_tkde_dom ain-driven.pdf http://www.computer.org/portal/cms_docs_tran sactions/transactions/tkde/CFP/cfp_tkde_dom ain-driven.pdf

13. Program 2:00 pmOpening address 2:10 pmKeynote speech Domain Driven Data Mining (D 3 M) by Longbing Cao, University of Technology, Sydney, Australia 2:40 pmSession I S2211: Food Sales Prediction: "If Only It Knew What We Know“, by Patrick Meulstee and Mykola Pechenizkiy S2205: Parameter Tuning for Differential Mining of String Patterns, by Jeremy Besson, Christophe Rigotti, Ieva Mitasiunaite, and Jean-Francois Boulicaut S2202: Discovering Implicit Redundancies in Network Communications for Detecting Inconsistent Values, by Bogdan Nassu, Takashi Nanya, and Hiroshi Nakamura S2208: Identification of Causal Variables for Building Energy Fault Detection by Semi-supervised LDA and Decision Boundary Analysis, by Keigo Yoshida, Minoru Inui, Takehisa Yairi, Kazuo Machida, Masaki Shioya, and Yoshio Masukawa 4:00 pmCoffee Break 4:15pmSession II S2206: Actionable Knowledge Discovery for Threats Intelligence Support using a Multi- Dimensional Data Mining Methodology, by Olivier Thonnard and Marc Dacier DM422: One-class Classification of Text Streams with Concept Drift, by Xue Li and Yang Zhang DM830: Post-Processing of Discovered Association Rules using Ontologies, by Claudia Marinica, Fabrice Guillet, and Henri Briand S2212: Behavior Informatics and Analytics: A New and Promising Area, by Longbing Cao DM424: TransRank: A Novel Algorithm for Transfer of Rank Learning, by Depin Chen, Jun Yan, Gang Wang, and Weiguo Fan DM698: Scoring Models for Insurance Risk Sharing Pool Optimization, by Nicolas Chapados, Charles Dugas, Pascal Vincent, and Rejean Ducharme