From: motoda@harl.hitachi.CO.JP (Hiroshi Motoda)
Newsgroups: fj.ai,fj.meetings
Subject: Call for Participation of JKAW92
Date: 12 Sep 92 02:11:06 GMT
Followup-To: fj.ai
Distribution: fj
Organization: Advanced Research Laboratory, Hitachi, Ltd



    The 2nd Japanese Knowledge Acquisition for Knowledge-Based
    Systems Workshop $B#J#K#A#W#9#2(J $B;22C0FFb(J

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$B!!!!(JCo-Chairmen: Riichiro Mizoguchi, Hiroshi Motoda,
 $B!!!!!!!!!!!!!!!!(JBrian Gaines, John Boose, and Ross Quinlan

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	(Phone)06-877-5111(ext. 3565)$B!?(J06-876-2905$B!J8&5f<<D>DL!K(J
	(Fax)06-877-4977
	(Email)miz@ei.sanken.osaka-u.ac.jp

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	(Phone)0492-96-6111(ext. 225)
	(Fax)0492-96-6006
	(Email)motoda@harl.hitachi.co.jp


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                 $B%W%m%0%i%`(J

        $B>7BT9V1i!J1w?@8M9q:]2q5D>l!K(J

$B8@!!8l!'1Q8l!JA49V1iF1;~DLLuIU$-!K(J

November 9th 

10:00-10:15	Opening session 
10:15-11:30     Integrating KA models for group decision support by John
                Boose
11:30-13:00	Lunch 

13:00-14:15	KADS2: Model-driven knowledge acquisition
                methodology(tentative) by Bob Wielinga 

14:15-15:30     End-user configuration of applications by Luc Steels

15:30-16:00     Coffee break 

16:00-17:15	An analysis of the role of operational modeling
                languages in the development of knowledge-based
                systems by Marc Linster 

17:30-19:00	Banquet

November 10th

 9:00-10:15	An interlingua for knowledge interchange: General
                requirements and a proposed language specification
                by Tom Gruber

10:15-11:30	Common ontologies as a mechanism for software reuse
                by Tom Gruber

11:30-13:00	Lunch

13:00-14:15	Knowledge acquisition from protein data by learning
		algorithms by Setsuo Arikawa

14:15-15:30	Learning control rules from examples by Claude Sammut

15:30-16:00	Coffee break 

16:00-17:15	Integration of machine learning and knowledge acquisition
		by Sholom Weissb

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                $B0lHL9V1i!J1wF|N)4pAC8&!K(J

$B8@!!8l!'1Q8l!JDLLu$J$7!K(J

Nov. 12

 8:00          Bus to ARL from Hotel

 9:30- 9:50    Opening

             Induction(1)

 9:50-10:25    Ripple-Down-Rules as a Mediating Representation in
               Interactive Induction by Jason Catlett

10:25-11:00    Learning From Noisy Data with Linear Pjrogramming
               by Takefumi Yamazaki, Shigeo Kaneda and Hiroshi
                Tsumura

11:00-11:15    Coffee break

             Task Ontology and Modeling

11:15-11:50    Task Ontology And Its Use in a Task Analysis Interview
               System by Riichiro Mizoguchi, Yuri Tijerino and
               Mitsuru Ikeda

11:50-12:25    Modeling Job Assignment Problems Based on Task Ontology
               by Toshiyuki Hama, Masahiro Hori and Yuichi Nakamura

12:25- 1:00    Methodology for Configuring Scheduling Engines with
               Task-Specific Components by Masahiro Hori, Yuichi
               Nakamura and Toshiyuki Hama

 1:00- 2:15    Lunch

             Knowledge Reuse

 2:15- 2:50    Knowledge Cassette for Customizing Knowledge
               Acquisition Tools by Dai Araki, Shoichi Kojima and
               Takeshi Kohno

 2:50- 3:25    Identifying Reusable Problem-Solving Knowledge as
               Task-Specific Components by Yuichi Nakamura, Masahiro
               Hori and Toshiyuki Hama

 3:25- 3:40    Coffee break

             Abstraction

 3:40- 4:15    Acquiring (Ir)relevance Knowledge for Problem Solving
               by Alon Y. Levy, Hiroshi Motoda and Yumi Iwasaki

 4:15- 4:50    Automatic Knowledge Reformation by Ken'ichi Yoshida and
               Hiroshi Motoda

 4:50- 6:20    Demonstrations

 5:20-         Bus to ARL (for accompanying persons)

 6:30- 9:00    Banquet at ARL's guest house

 9:00-         Bus to Hotel

Nov. 13

 8:00          Bus to ARL from Hotel

             Knowledge Base Refinement and and Validation

 9:15- 9:50    An Integrated Knowledge Acquisition Tool for
               Classification Problems by Yoshiyuki Koseki, Midori
               Tanaka and Yoichiro Nakakuki

 9:50-10:25    KBRLAB: An Environment for the Development and
               Validation of Refinement Systems by Nitin Indurkhya,
               Sholom M. Weiss and Peter Politakis

10:25-11:00    A Knowledge Acquisition System Using Version Space
               by Kenichi Hagiwara, Takeshi Terasaki and Teruaki
               Matsui

11:00-11:15    Coffee break

             Misc.(CBR, Causality and Discovery)

11:15-11:50    What a CBR System Learns: Performance Evaluation
               of a Case-Based Information by TERANO, Takao and
               NABETA, Shigeko

11:50-12:25    Modelling with Context-Dependent Causality
               by Maria Lee, Paul Compton and Bob Jansen

12:25- 1:00    Knowledge Discovery and Evolution in Databases:
               A Unified Approach by Jong P. Yoon

 1:00- 2:15    Lunch

             Induction(2)

 2:15- 2:50    Constituting Neural Networks by Decision Tree Induction:
               An experimental approach of Neuro-KAISER by Katsuhiko
               Tsujino and Shogo Nishida

 2:50- 3:25    CNN: Integrating Knowledge Elicitation and Machine Learning
               by Nigel Major and Nigel Shadbolt

 3:25- 3:40    Coffee break

             Knowledge Acquisition Managament

 3:40- 4:15    MAFKAP: A Management Framework for the Knowledge
               Acquisition Process by YUE, Nora Y L and COX, Benita

 4:15- 4:50    On Cognitive Invariants Between Different Levels of Scale
               by Alain T Rappaport

 4:50- 6:00    Demonstration

 6:00- 6:10    Concluding remark

 6:30-         Bus to Hotel
Xref: sparky fj.ai:741 fj.sci.misc:794