Selected papers in
ICML2005 4th International Workshop on Chance Discovery: From Data Interaction to Scenario Creation (CDWS4)

August 11, 2005

Room: HS V
University of Bonn
Regina-Pacis-Weg 3 53113 Bonn, Germany

Chairs: Akinori Abe, ATR Intelligent Robotics and Communication Labs, Japan
Ruediger Oehlmann, Kingston Univ. London, UK
Yukio Ohsawa, the Univ. of Tokyo, Japan

8.45--8.50 Opening Remarks
Session 1: Methods of Chance Discovery
8.50--9.15 Matsushita M. and Shirai Y. Supporting Exploration and Reflection in Exploratory Data Analysis
9.15--9.40 Sakakibara T. and Ohsawa Y. Generation of Multiple KeyGraphs with Different Complexity from One Data Set
9.40--10.05 Tsumoto S. Detection of Rules' Anomalies Using Rule Induction and Multidimensional Scaling
10.05--10.30 Ohsawa Y. and Matsumura N. Extracting Essence from Sequential Data based on Event Influence
10.30--11.00 Coffee Break
11.00--11.25 Kushiro N. and Ohsawa Y. A Scenario Acquisition Method with Multi-Dimensional Hearing and Hierarchical
11.25--11.50 Natarajan R. and Shekar B. A Tightness-based Heuristic for Clustering Association Rules
Session 2: Socio-Cognitive Aspects of Chance Discovery
11.50--12.15 Magnani L. Scenario Creation and the Disembodiment of Mind
12.15--12.40 Bergner D., Eris O. and Jung M. Dialogue-Based Metrics of Design Team Learning and Discovery
12.40--14.00 Lunch Break
14.00--14.25 Nara Y. A Study on the Trust as the Base of Chance Discovery: Focusing on the Both Aspects of Input and Output of Trust
14.25--14.50 Oehlman R. The Symbolic-Instrumental Dichotomy of Trust-Enhancing Strategies in Collaborative Chance Discovery
14.50--15.15 Nyu Y., Ohsawa Y., Nishio C., and Nakamura Y. Influence of Externalization on Breakdown Process in Appreciating Artwork
15.15--15.40 Shoji H. Self-Discovery During Job-Hunting Process
15.40--16.05 Raval G. and Pal A. Moving Towards Human-Machine Interface
16.05--16.30 Coffee Break
Session 3: Scenario Emergence and its Application
16.30--16.55 Abe A., Naya F., Ozaku H.I., Kuwahara N., and Kogure K. Scenario Violation in Nursing Activities
16.55--17.20 Yada K. and Tanaka S. Scenario Representation in Consumer Behaviour
17.20--17.45 Murata S. On the Scenario of Customer's Purchase Action Got by Analyzing Customer Card
17.45--18.10 Barsode S., Naga L., and Rege S. Machine Learning, Fuzzy Logic and Chance Discovery: Applications in Credit Risk Modeling With Special Reference to Indian Banking