DM: Call for Participation (PAKDD-99)

[pakdd99]

                         ********************
                         *  P A K D D ' 99  *
                         ********************
 
   The Third Pacific-Asia Conference on Knowledge Discovery and Data 
Mining
 
                     Xiangshan Hotel, Beijing, China

                           April 26-28, 1999

              C A L L   F O R   P A R T I C I P A T I O N
 
        Home Page: http://ain2.ai.csse.yamaguchi-u.ac.jp/pakdd99

        ********************************************************
        *  A copy of the registration form is attached below.  *
        *  You can also register at the conference.            *      
    
        ********************************************************


INTRODUCTION
============

PAKDD-99 provides an international forum for the sharing of original
research results and practical development experiences among
researchers and application developers from different KDD related
areas such as machine learning, databases, statistics, knowledge
acquisition, data visualization, knowledge-based systems, soft
computing, and high performance computing.  It follows the success of
PAKDD-97 held in Singapore in 1997 and PAKDD-98 held in Australia in
1998 by bringing together participants from universities, industry and
government.

PAKDD-99 encourages both new theory/methodologies and real world
applications, and covers broad and diverse topics in data mining and
knowledge discovery.  The technical sessions include: Association
Rules Mining; Feature Selection and Generation; Mining in Semi,
Un-structured Data; Interestingness, Surprisingness, and Exceptions;
Rough Sets, Fuzzy Logic, and Neural Networks; Induction,
Classification, and Clustering; Causal Model and Graph-Based Methods;
Visualization; Agent-Based, and Distributed Data Mining; Advanced
Topics and New Methodologies.

Of the 158 submissions, we accepted 29 regular papers and 37 short
papers for presentation at the conference and for publication in the
conference proccedings by Springer-Verlag as a book, titled
`Methodologies for Knowledge Discovery and Data Mining' 
(Lecture Notes in Artificial Intelligence 1574).  
In addition, over 20 papers were accepted for poster presentation.

The PAKDD-99 program is further supplemented by two invited
speakers: Won Kim and Hiroshi Motoda, a special session on Emerging
KDD Technology (Speakers: Zdzislaw Pawlak, Philip Yu, T.Y. Lin,
Hiroshi Tsukimoto), and a panel session on Knowledge Management in
Data Mining (Chair: Xindong Wu; Panelists: Rao Kotagiri, Zhongzhi Shi,
Jan M. Zytkow).

Two tutorials: Automated Discovery - Combining AI, Statistics and
Theory of Knowledge by Jan M. Zytkow, Quality Data and Effective
Mining by Hongjun Lu, and a workshop on Knowledge Discovery from
Advanced Databases organized by Mohamed Quafafou and Philip Yu, are
also offered to all conference participants on April 26.


ADVANCE PROGRAM OF PAKDD-99
###########################

April 26, Monday
=================

Tutorials:
----------

  Morning (9:00 - 12:00): 
    "Automated Discovery: Combining AI, Statistics and Theory of 
Knowledge" 
     Jan Zytkow (University of North Carolina, USA)

  Afternoon (14:00 - 17:00): 
    "Quality Data and Effective Mining" 
    Hongjun Lu (Hong Kong University of Science and Technology) 

Workshop:
---------

The PAKDD Workshop on Knowledge Discovery from Advanced Databases 
    Full Day: http://www.sciences.univ-nantes.fr/kdad99
    Co-chairs: Mohamed Quafafou (University of Nantes, France) and 
               Philip Yu (IBM T.J. Watson Research Center, USA)


PAKDD Steering Committee Meeting (18:00 - )


April 27, Tuesday
==================

8:30 - 8:45
Opening Ceremony
Introduction: Bo Zhang      (Conference Chair, Tsinghua University, 
China)
              Setsuo Ohsuga (Conference Chair, Waseda University, 
Japan)

8:45 - 9:45 
Keynote Talk: Won Kim (Cyber Database Solutions, USA) 
KDD as an Enterprise IT Tool: Reality and Agenda 


9:45 - 10:00
Break

-----------------------------
10:00 - 12:00  
Session 1: Association Rules  
-----------------------------

10:00-10:20 
Mining Association Rules on Related Numeric Attributes
by Xiaoyong Du, Zhibin Liu, Naohiro Ishii 
(Nagoya Institute of Technology, Japan)

10:20-10:40
LGen - A Lattice-Based Candidate Set Generation Algorithm 
for I/O Efficient Association Rule Mining
by Chi-Lap Yip, K.K. Loo, Ben Kao, David W. Cheung, C.K. Cheng
(University of Hong Kong)

10:40-11:00
Extending the Applicability of Association Rules
by Karthick Rajamani (Rice University, USA)
   Sam Sung (National University of Singapore) 
   Alan Cox (Rice University, USA)

11:00-11:20
An Efficient Approach for Incremental Association Rule Mining
by Pauray S.M. Tsai (Ming Hsin Institute of Technology, Taiwan)
   Chih-Chong Lee, Arbee L.P. Chen (National Tsinghua University, 
Taiwan)

11:20-11:40
Association Rules in Incomplete Databases
by Marzena Kryszkiewicz (Warsaw University of Technology, Poland)

11:40-12:00
Visually Aided Exploration of Interesting Association Rules
by Bing Liu, Wynne Hsu, Ke Wang, Shu Chen
(National University of Singapore)

----------------------------------------------------
10:00 - 12:00 
Session 2: Induction, Classification, and Clustering 
-----------------------------------------------------

10:00-10:20
Characterization of Default Knowledge in Ripple Down Rules Method
by Takuya Wada, Tadashi Horiuchi, Hiroshi Motoda, Takashi Washio
(Osaka University, Japan)

10:20-10:40
Improving the Performance of Boosting for Naive Bayesian 
Classification
by Kai Ming Ting, Zijian Zheng (Deakin University, Australia)

10:40-11:00
Convex Hulls in Concept Induction
by D.A. Newlands, G.I. Webb (Deakin University, Australia)

11:00-11:15
A Lazy Model-Based Algorithm for On-Line Classification
by Gabor Melli (Simon Fraser University, Canada)

11:15-11:30 
An Efficient Space-Partitioning Based Algorithm 
for the K-Means Clustering
by Khaled Alsabti (King Saud University)
   Sanjay Ranka (University of Florida, USA)
   Vineet Singh (Hitachi America Ltd., USA)

11:30-11:45
A Fast Clustering Process for Outliers and Remainder Clusters
by Chih-Ming Su, Shian-Shyong Tseng, Mon-Fong Jiang, Joe C.S. Chen
(National Chiao Tung University, Taiwan)

11:45-12:00
Optimising the Distance Metric in the Nearest Neighbour Algorithm 
on a Real-world Patient Classification Problem
by Hongxing He   (Health Insurance Commission, Australia)
   Simon Hawkins (CRC, CSIRO, Australia)

12:00 - 13:30
Lunch

(Business Meeting at 13:00 - 13:30)

-------------------------------------------
13:30 - 14:50 
Special Session on Emerging KDD Technology
-------------------------------------------

13:30-13:50
Data Mining: A Rough Set Perspective
by Zdzislaw Pawlak (Polish Academy of Sciences, Poland)

13:50-14:10
Trends and Directions in Data Mining
by Charu C. Aggarwal, Philip S. Yu (IBM T.J. Watson Research Center, 
USA)

14:10-14:30
Data Mining: Granular Computing (GrC) Approach 
by T.Y. Lin (San Jose State University, USA)

14:30-14:50
Rule Extraction from Prediction Models 
by Hiroshi Tsukimoto  (Toshiba Corporation, Japan)

14:50 - 15:00 
Break


-------------------------------------------
15:00 - 16:25 
Session 3: Feature Selection and Generation 
-------------------------------------------

15:00-15:20
Induction as Pre-Processing
by Xindong Wu (Colorado School of Mines, USA)

15:20-15:40
Stochastic Attribute Selection Committees with Multiple Boosting: 
Learning More Accurate and More Stable Classifier Committees
by Zijian Zheng, Geoffrey I. Webb (Deakin University, Australia) 

15:40-15:55
On Information-Theoretic Measures of Attribute Importance
by Y.Y. Yao, S.K.M. Wong, C.J. Butz (University of Regina, Canada)

15:55-16:10
A Technique of Dynamic Feature Selection 
Using the Feature Group Mutual Information
by Kee-Cheol Lee (HongIk University, Korea)

16:10-16:25
A Data Pre-Processing Method Using Association Rules of Attributes
for Improving Decision Tree
by Masahiro Terabe (Mitsubishi Research Institute, Japan) 
   Osamu Katai, Tetsuo Sawaragi (Kyoto University, Japan)
   Takashi Washio, Hiroshi Motoda (Osaka University, Japan)

---------------------------------------------------
15:00 - 16:25 
Session 4: Agent-Based, and Distributed Data Mining 
---------------------------------------------------

15:00-15:20
Probing Knowledge in Distributed Data Mining
by Yike Guo, Janjao Sutiwaraphun (Imperial College, UK)

15:20-15:40
Discovery of Equations and the Shared Operational
Semantics in Distributed Autonomous Databases
by Zbigniew W. Ras, Jan M. Zytkow
(University of North Carolina, USA)

15:40-15:55
The Data Mining and the Technology of Agents to Fight 
the Illicit Electronic Messages
by A. Zighed (Universite Lumiere Lyon 2, France)
   M. Cote, N. Troudi (Universite Laval, Canada)

15:55-16:10
Knowledge Discovery in Sports Finder: an Agent to
extract sports results from the Web
by Hongen Lu, Leon Sterling, Alex Wyatt
(University of Melbourne, Australia)

16:10-16:25
Event Mining with Event Processing Networks
by Louis Perrochon, Walter Mann, Stephane Kasriel, David C. Luckham
(Stanford University, USA)
 

-------------------------------------------------------
16:30 - 17:35 
Session 5: Rough Sets 
-------------------------------------------------------

16:30-16:50
Automated Discovery of Plausible Rules based on Rough Sets 
and Rough Inclusion
by Shusaku Tsumoto (Tokyo Medical and Dental University, Japan)

16:50-17:05
Discernibility System in Rough Sets
by Zongtian Liu, Zhipeng Xie
(Hefei University of Technology, China)

17:05-17:20 
Sustainability Knowledge Mining from Human Development Database
by Xuefei Wang (University of Science and Technology of China)
   Rusong Wang, Jue Wang (Chinese Academy of Sciences)

17:20-17:35
Rule Discovery in Databases with Missing Values based on Rough Set 
Model
by Shusaku Tsumoto (Tokyo Medical and Dental University, Japan)

----------------------------------------------------------
16:30 - 17:30 
Session 6: Interestingness, Surprisingness, and Exceptions
----------------------------------------------------------

16:30-16:50
Evolutionary Hot Spots Data Mining: An Architecture for
Exploring for Interesting Discoveries
by Graham Williams (CRC, CSIRO, Australia)

16:50-17:10
Efficient Search of Reliable Exceptions
by Huan Liu   (National University of Singapore)
   Hongjun Lu (Hong Kong University of Science and Technology) 
   Ling Feng  (Hong Kong Polytechnic University)
   Farhad Hussain (National University of Singapore)

17:10-17:30
Heuristics for Ranking the Interestingness of Discovered Knowledge
by Robert J. Hilderman, Howard J. Hamilton 
  (University of Regina, Canada)


--------------
17:30 - 18:30 
Poster
--------------

19:00
Banquet 
(Best Paper Award Ceremony) 


April 28, Wednesday
===================

8:30 - 9:30
Invited Talk: Hiroshi Motoda (Osaka University, Japan) 
Computer Assisted Discovery of First Principle Equations 
from Numeric Data 


9:30 - 9:45
Break

---------------------------------------------
9:45 - 11:10
Session 7: Mining in Semi, Un-structured Data
---------------------------------------------

9:45-10:05
An Algorithm for Constrained Association Rule Mining 
in Semi-structured Data
by Lisa Singh, Bin Chen (Northwestern University, USA)
   Rebecca Haight (Data Harbor, Inc. USA)
   Peter Scheuermann (Northwestern University, USA)

10:05-10:25
Incremental Mining of Schema for Semi-structured Data
by Aoying Zhou, Jin Wen, Shuigen Zhou, Zenping Tian
(Fudan University, China)

10:25-10:40
Discovering Structure from Document Databases
by Mon-Fong Jiang, Shian-Shyong Tseng, Chung-Jiun Tsai
(National Chiao Tung University, Taiwan)

10:40-10:55
Combining Forecasts from Multiple Textual Data Sources
by Vincent Cho, Beat Wuthrich
(Hong Kong University of Science and Technology)

10:55-11:10
Domain Knowledge Extracting in a Chinese Natural Language Interface 
to Databases: NChiql
by Xiaofeng Meng, Yong Zhou, Shan Wang
(People's University of China)

------------------------------------------------
9:45 - 11:15
Session 8: Causal Model and Graph-Based Methods
------------------------------------------------

9:45-10:05
A Minimal Causal Model Learner
by Honghua Dai (Deakin University, Australia) 

10:05-10:25
Efficient Graph-Based Algorithm for Discovering and 
Maintaining Knowledge in Large Databases
by K. L. Lee, Guanling Lee, Arbee L.P. Chen
(National Tsinghua University, Taiwan)

10:25-10:45
Basket Analysis for Graph Structure Data
by Akihiro Inokuchi, Takashi Washio, Hiroshi Motoda (Osaka U., Japan)
   Kouhei Kumasawa, Naohide Arai (Recruit Co., Ltd., Japan)

10:45-11:00
The Evolution of Causal Models: A Comparison of 
Bayesian Metrics and Structure Priors
by Julian R. Neil, Kevin B. Korb (Monash University, Australia)

11:00-11:15
KD-FGS: A Knowledge Discovery System from Graph Data 
Using Formal Graph System
by Tetsuhiro Miyahara, Tomoyuki Uchida (Hiroshima City U., Japan)
   Tetsuji Kuboyama (University of Tokyo, Japan)
   Tatsuya Yamamoto, Kenichi Takahashi, Hiroaki Ueda 
   (Hiroshima City U., Japan)


-----------------------------
11:15 - 12:15
Session 9: Association Rules 
-----------------------------

11:15-11:30
Parallel SQL Based Association Rule Mining on Large Scale PC Cluster:
Performance Comparison with Directly Coded C Implementation
by Iko Pramudiono, Takahiko Shintani, Takayuki Tamura, Masaru 
Kitsuregawa
(University of Tokyo, Japan)

11:30-11:45
H-Rule Mining in Heterogeneous Databases
by Yuping Yang, Mukesh Singhal (Ohio State University, USA)

11:45-12:00
An Improved Definition of Multidimensional, Inter-transaction 
Association Rule
by Aoying Zhou, Shuigeng Zhou, Jin Wen, Zenping Tian
(Fudan University, China)

12:00-12:15
Incremental Discovering Association Rules: A Concept Lattice Approach
by Keyun Hu, Yuchang Lu, Chunyi Shi (Tsinghua University, China)

------------------------------------------------
11:15 - 12:15
Session 10: Advanced Topics and New Methdologies 
------------------------------------------------

11:15-11:35
An Analysis of Quantitative Measures Associated with Rules
by Y.Y. Yao   (University of Regina, Canada)
   Ning Zhong (Yamaguchi University, Japan)

11:35-11:55
DVIZ: A System for Visualizing Data Mining
by Jianchao Han, Nick Cercone (University of Waterloo, Canada)

11:55-12:15
A Strong Relevant Logic Model of Epistemic Processes 
in Scientific Discovery
by Jingde Cheng (Kyushu University, Japan)


12:30 - 13:30
Lunch

-------------------------------------------
13:30 - 15:10
Session 11: Neural Networks and Fuzzy Logic  
-------------------------------------------

13:30-13:50
Neural Network Based Classifiers for A Vast Amount of Data
by Ling Zhang (Anhui University, China)
   Bo Zhang   (Tsinghua University, China)

13:50-14:10
Automatic Labeling of Self-Organizing Maps: 
Making a Treasure-Map Reveal its Secrets
by Andreas Rauber, Dieter Merkl
(Technische Universitat Wien, Austria)

14:10-14:25
Accuracy Tuning on Combinatorial Neural Model
by Hercules A. Prado, KArla F. Machado, Sandra R. Frigeri, Paulo M. 
Engel
(Federal University of Rio Grande do Sul, Brazil)

14:25-14:40
A Situated Information Articulation Neural Network: VSF Network
by Y. Kakemoto, S. Nakasuka (University of Tokyo, Japan)

14:40-14:55
Neural Method for Detection of Complex Patterns in Databases
by Chao Deng, Fanlun Xiong
(University of Science and Technology of China)

14:55-15:10
An Induction Algorithm Based on Fuzzy Logic Programming
by Daisuke Shibata, Nobuhiro Inuzuka (Nagoya Institute of Tech., 
Japan)
   Shohei Kato (Toyota National College of Technology, Japan)
   Tohgoroh Matsui, Hidenori Itoh (Nagoya Institute of Tech., Japan)

-----------------------------------------------------
13:30 - 15:05
Session 12: Induction, Classification, and Clustering
------------------------------------------------------

13:30-13:50                 
Mining Classification Knowledge Based on Cloud Models
by Jianhua Fan (Nanjing Communication Eng, Institute, China)
   Deyi Li     (Institute of Electronic System Eng., China)

13:50-14:10
Robust Clustering of Large Geo-referenced Data Sets
by Vladimir Estivill-Castro, Michael E.Houle
(University of Newcastle, Australia)

14:10-14:30
A Fast Algorithm for Density-Based Clustering in Large Database
by Bo Zhou (Zhejiang University)
   David W. Cheung, Ben Kao (University of Hong Kong)

14:30-14:50
Classifying Unseen Cases with Many Missing Values
by Zijian Zheng (Deakin University, Australia)
   Boon Toh Low (The Chinese University of Hong Kong)

14:50-15:05
Study of a Mixed Similarity Measure for 
Classification and Clustering
by Tu Bao Ho, Ngoc Binh Nguyen, Takafumi Morita
  (Japan Advanced Institute of Science and Technology, Japan)


15:05 - 15:20
Break

------------------------------------------------
15:20 - 16:20
Session 13: Advanced Topics and New Methdologies 
-------------------------------------------------

15:20-15:35
Prediction Rule Discovery based on Dynamic Bias Selection
by Einoshin Suzuki and Toru Ohno
   (Yokohama National University, Japan)

15:35-15:50
Ordered Estimation of Missing Values
by Oscar Ortega Lobo, Masayuki Numao
  (Tokyo Institute of Technology, Japan)

15:50-16:05
Discovering Conceptual Differences among Different People 
via Diverse Structures
by Tetsuya Yoshida, Teruyuki Kondo, Shogo Nishida
   (Osaka University, Japan)

16:05-16:20
Preserve Discovered Linguistic Patterns Valid 
in Volatility Data Environment
by Xuemei Shi, Man-Chung Chan (Hong Kong Polytechnic University)
   Deyi Li (Institute of Electronic System Eng., China)

------------------------------------------------
15:20 - 16:20
Session 14: Advanced Topics and New Methdologies 
-------------------------------------------------

15:20-15:35
Discretization of Continuous Attributes for Learning Classification 
Rules
by Aijun An, Nick Cercone (University of Waterloo, Canada)

15:35-15:50  
BRRA: A Based Relevant Rectangle Algorithm 
for mining relationships in databases
by Sadok Ben Yahia (Sciences Faculty of Tunis, Tunisia)
   Ali Jaoua (King Fahd University, Saoudi Arabia)

15:50-16:05    
Mining Functional Dependency Rule of Relational Database
by Xiaopeng Tao, Ning Wang, Shuigen Zhou, Aoying Zhou, Yunfa Hu  
  (Fudan University, China)

16:05-16:20  
Time-series Prediction with Cloud Models in DMKD
by Rong Jiang (Institute of Communication Eng., China)
   Deyi Li    (Institute of Electronic System Eng., China)
   Hui Chen   (Institute of Communication Eng., China)


16:20 - 16:30
Break

16:30 - 17:30:
Panel Discussion: Knowledge Management in Data Mining 
Chair: Xindong Wu (Colorado School of Mines, USA)
Panelists: Rao Kotagiri (University of Melbourne, Australia)
           Zhongzhi Shi (ICT, Chinese Academy of Sciecnes)
           Jan Zytkow   (University of North Carolina, USA) 


18:30
Program Committee Dinner

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%


                    REGISTRATION FORM
                    =================

                PAKDD-99, April 26-28, 1999
              Xiangshan Hotel, Beijing, China
 
Conference Registration Fee:
 
                   Before April 10, 1999    After April 10, 1999 
----------------------------------------------------------------
Regular (*)             JPY 50,000              JPY 55,000
Student (**)            JPY 35,000              JPY 40,000

(*) The registration fee includes tutorials, workshop, 
three lunches, refreshments in coffee breaks, and the proceedings.

The banquet is included for regular registration only. 
Cost is JPY 3,000 for student registrations and/or 
an additional banquet ticket. Moreover, cost is JPY 1,500 
for an additional lunch ticket (one lunch).

(**) Full-time students. Students must submit a verification
letter of full-time status from the department head.


PLEASE TYPE OR PRINT:
 
Title: ______ First Name: ______________ Surname: _________________
 
Affiliation:_______________________________________________________
 
Address: __________________________________________________________
 
City: _________________ State: __________  Post/Zip Code: _________
 
Country: __________________________________________________________
 
Phone: ___________________________ Fax: ___________________________
 
Email: ____________________________________________________________
 
 
                              Conference Fee: ____________________
 
                    Banquet and/or lunches 
                   (for student registration 
                    and/or additional tickets):____________________

  
                                Total Payment: ____________________
 

Payment of registration fee should be only in Japanese Yen (JPY).
You may choose one of payment ways below.

(1) Payment is made in Japanese Yen by cheque (check) 
    and accompanies the registration form.  

(2) Payment is transferred to the account:

    Acc. number: 604-0337539 of PAKDD99
                 in the Tokuyama Branch of the Bank of 
Tokyo-Mitsubishi

(3) VISA Card or Master Card are acceptable for the payment of 
    registration fee.

If you wish to pay by credit card, please complete the following:
 
Select one: ___ VISA  ___ Mastercard   Expiration Date: __________
 
Print name exactly as shown on card: _____________________________
 
Card Number: _____________________________________________________
 
Cardholder's signature: _________________________ Date: __________


Written cancellations will be NO refund.
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 
Please return registration form and fee to: 

Prof. Ning Zhong (PAKDD-99) 
Dept. of Computer Science and Systems Eng.    
Faculty of Engineering, Yamaguchi University 
Tokiwa-Dai, 2557, Ube 755, Japan

Tel&Fax: +81-836-35-9949  
Email: zhong@ai.csse.yamaguchi-u.ac.jp 

---------------------------------------------------------------------