DDDM 2008: The 2nd International Workshop on Domain Driven Data Mining

Philip S. Yu, Yanchang Zhao, Graham Williams, Carlos Soares

Data Sciences & Knowledge Discovery Research Lab 2

Outline

DDDM: Domain Driven Data Mining

DDDM 2007DDDM 2008

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.

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.

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.

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 ChairsChengqi 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

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/ 39 submissions from 12 countries (including

papers forwarded from main conference) 10 papers accepted, with an acceptance rate

of 26%

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

Data Sciences & Knowledge Discovery Research Lab 9

Host

Data Sciences & Knowledge Discovery Research Labhttp://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

Data Sciences & Knowledge Discovery Research Lab 10

Program Committee

Ronnie Alves Universidade do Minho, PortugalElena Baralis Politecnico di Torino, ItalyDavid Bell Queen's University Belfast, UKPetr Berka University of Economics of Prague, Czech RepublicJean-Francois Boulicaut INSA Lyon, FranceLongbing Cao University of Technology, Sydney, AustraliaPeter Christen The Australian National University, AustraliaPaulo Cortez University of Minho, PortugalGuozhu Dong Wright State University, USAWarwick Graco Australian Taxation Office, AustraliaJoshua Zhexue Huang The University of Hong Kong, Hong KongAlexandros Kalousis The Universtity of Geneva, SwitzerlandWalter Kosters Leiden University, The NetherlandsChristopher Leckie The University of Melbourne, AustraliaChunhung Li Hong Kong Baptist University, Hong KongXue Li The University of Queensland, AustraliaTsau Young Lin San Jose State University, USA

Data Sciences & Knowledge Discovery Research Lab 11

Program Committee (cont.)

Donato Malerba University of Bari, ItalyEngelbert Mephu Nguifo Universite d'Artois, FranceNgoc Thanh Nguyen Wroclaw University of Technology, PolandArlindo Oliveira IST/INESC-ID, PortugalAlexandre Plastino Universidade Federal Fluminense, BrazilKulathur S. Rajasethupathy State University of New York, USAYidong Shen Chinese Academy of Sciences, ChinaDan Simovici University of Massachusetts at Boston, USAWei Wang Fudan University, ChinaJeffrey Xu Yu The Chinese University of Hong Kong, Hong

KongCarlo Zaniolo University of California, Los Angeles, USAJustin Zhan Carnegie Mellon University, USAChengqi Zhang University of Technology, Sydney, AustraliaHuaifeng Zhang University of Technology, Sydney, AustraliaMengjie Zhang Victoria University of Wellington, New ZealandShichao Zhang Guangxi Normal University, ChinaZhi-Hua Zhou Nanjing University, China

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-D

DDM.doc http://www.computer.org/portal/cms_docs_tran

sactions/transactions/tkde/CFP/cfp_tkde_domain-driven.pdf

Program2:00 pm

Opening address

2:10 pm

Keynote speechDomain Driven Data Mining (D3M) by Longbing Cao, University of Technology, Sydney, Australia

2:40 pm

Session IS2211: Food Sales Prediction: "If Only It Knew What We Know“, by Patrick Meulstee and Mykola PechenizkiyS2205: Parameter Tuning for Differential Mining of String Patterns, by Jeremy Besson, Christophe Rigotti, Ieva Mitasiunaite, and Jean-Francois BoulicautS2202: Discovering Implicit Redundancies in Network Communications for Detecting Inconsistent Values, by Bogdan Nassu, Takashi Nanya, and Hiroshi NakamuraS2208: 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 pm

Coffee Break

4:15pm

Session IIS2206: Actionable Knowledge Discovery for Threats Intelligence Support using a Multi-Dimensional Data Mining Methodology, by Olivier Thonnard and Marc DacierDM422: One-class Classification of Text Streams with Concept Drift, by Xue Li and Yang ZhangDM830: Post-Processing of Discovered Association Rules using Ontologies, by Claudia Marinica, Fabrice Guillet, and Henri BriandS2212: Behavior Informatics and Analytics: A New and Promising Area, by Longbing CaoDM424: TransRank: A Novel Algorithm for Transfer of Rank Learning, by Depin Chen, Jun Yan, Gang Wang, and Weiguo FanDM698: Scoring Models for Insurance Risk Sharing Pool Optimization, by Nicolas Chapados, Charles Dugas, Pascal Vincent, and Rejean Ducharme