AIList-REQUEST@AI.AI.MIT.EDU (AIList Moderator Nick Papadakis) (05/24/88)
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Date: 13 May 88 02:57:07 GMT
From: kersch@gmu90x.gmu.edu (Larry Kerschberg)
Organization: George Mason University, Fairfax, Va.
Subject: Proceedings: 2nd Intl. Conf. on Expert Database Systems
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Second International Conference on Expert Database Systems
A limited number of the Proceedings from the
Second International Conference on Expert Database Systems are
available at a cost of $40. Tutorial notes are being sold for $15 each.
Please add a $5 handling charge for either the proceedings or any
combination of tutorials up to 4; add $2 handling fee for each
additional tutorial, $5 for each additional copy of the proceedings.
Tutorial Note Titles
_____ I-Logic and Databases by Dr. Carlo Zaniolo of MCC, Austin,
Texas
_____ II-Distributed Problem Solving in Knowledge/Data Environments
by Professor Victor Lesser of the University of Massachusetts at
Amherst
_____ III-Knowledge Representation and Data Semantics by Professor
John Mylopoulos of the University of Toronto
_____ IV-Acquisition of Knowledge from Data by Professor Gio
Wiederhold of Stanford University
Mail to : EDS Conference
Office of Conferences and Community Services
George Mason University
4400 University Drive
Fairfax, VA 22030, USA
Table of Contents
Session 1: Object-Oriented Systems
Chairman: Jacob Stein, Servio Logic, USA
Abstract Objects in an Object-Oriented Data Model
J. Zhu and D. Maier, Oregon Graduate Center, USA
The Design of KIVIEW: An Object-Oriented Browser
A. Motro, Univ. of Southern California, USA , A. D'Atri and L.
Tarantino, and Univ. of Rome, Italy
Towards a Unified View of Design Data and Knowledge Representation
B. Mitschang, Universitat Kaiserslautern, FRG
Session 2: Constraint Management
Chairman: Herve Gallaire, ECRC, FRG
Implementing Constraints in a Knowledge-Base
J.A. Wald, Schlumberger-Doll Research, USA
Update-Oriented Database Structures
L. Tucherman and A.L. Furtado, IBM Rio Scientific Center, Brazil
Distribution Design of Integrity ConstraintsX. Qian, Stanford
University, USA
Session 3: Panel Session: Constraint-Based Systems: Knowledge
about Data
Chairman: Matthew Morgenstern, SRI International, USA
Panelists: A. Borgida, Rutgers University, C. Lassez, IBM T.J. Watson
Research, D. Maier, Oregon Graduate Center, and G. Wiederhold,
Stanford University
Session 4: Expert Database System Architectures
Chairmen: Robert Meersman, Tilburg University, Netherlands and
Sushil Jajodia, NSF, USA
BERMUDA -- An Architectural Perspective on Interfacing Prolog to a
Database Machine
Y.E. Ioannidis, J. Chen, M.A. Friedman and M.M. Tsangaris, Univ. of
Wisconsin-Madison, USA
A Look at Loosely-Coupled Prolog/Database Systems
B. Napheys and D. Herkimer, Martin Marietta, USA
Combining Top Down and Bottom Up Computation in Knowledge Based
Systems
M. Nussbaum, Swiss Federal Institute of Technology (ETH),Switzerland
Session 5A: Knowledge/Data System Architectures
Chairmen: Roger King, Univ. of Colorado and Robert Abarbanel, Apple
Computer, Inc.
A Distributed Knowledge Model for Multiple Intelligent Agents
Y.P. Li, Jet Propulsion Laboratory, USA
The Relational Production Language: A Production Language for
Relational Databases
L.M.L. Delcambre and J.N. Etheredge, Univ. of Southwestern Louisiana,
USA
A Transaction Oriented Mechanism to Control Processing in a Knowledge
Base Management System
L. Raschid, Univ. of Maryland, USA and S.Y.W. Su, Univ. of Florida,
USA
Session 5B: Recursive Query Processing
Chairman: Tim H. Merrett, McGill University
Transitive Closure of Transitively Closed Relations
P. Valduriez and S. Khoshafian, MCC, USA
Transforming Nonlinear Recursion to Linear Recursion
Y.E. Ioannidis, Univ. of Wisconsin-Madison and E. Wong, UC-Berkeley,
USA
A Compressed Transitive Closure Technique for Efficient Fixed-Point
Query Processing
H.V. Jagadish, AT&T Bell Laboratories, USA
Session 6A: Learning and Adaptation in Expert Databases
Chairmen: Alex Borgida, Rutgers University and Don Potter, Univ. of
Georgia
An Automatic Improvement Processor for an Information Retrieval System
K.P. Brunner, Merit Technology, Inc. and R.R. Korfhage, Univ. of
Pittsburgh, USA
Supporting Object Flavor Evolution through Learning in an
Object-Oriented Database System
Q. Li and D. McLeod, Univ. of Southern California, USA
Implicit Representation of Extensional Answers
C.D. Shum and R. Muntz, UCLA, USA
Session 6B: Knowledge Management in Deductive Databases
Chairmen: Sham Navathe, Univ. of Florida
Deep Compilation of Large Rule Bases
T.K. Sellis and N. Roussopoulos, Univ. of Maryland, USA
Handling Knowledge by its Representative
C. Sakama and H. Itoh, ICOT, Japan
Integrity Constraint Checking in Deductive Databases using a Rule/Goal
Graph
B. Martens and M. Bruynooghe, Katholieke Universiteit Leuven, Belgium
Session 7: Panel Session: Knowledge Distribution and
Interoperability
Chairman: Michael Brodie, GTE Labs, USA
Panelists: Danny Bobrow, Xerox PARC, Carl Hewitt, MIT, Victor
Lesser, University of Massachusetts, Amherst, Stuart Madnick, MIT,
Dennis Tsichritzis, University of Geneva, Switzerland
Session 8: Intelligent Database Interfaces
Chairman: Larry Reeker, BDM Corporation
Musing in an Expert Database
S. Fertig and D. Gelernter, Yale University, USA
Cooperative Answering: A Methodology to Provide Intelligent Access to
Databases
F. Cuppens and R. Demolombe, ONERA-CERT, France
G+: Recursive Queries without Recursion
I.F. Cruz, A.O. Mendelzon and P.T. Wood, Univ. of Toronto, Canada
Session 9: Semantic Query Optimization
Chairman: Matthias Jarke, Univ. of Passau, FRG
Automatic Rule Derivation for Semantic Query Optimization
M.D. Seigel, Boston University, USA
A Metainterpreter to Semantically Optimize Queries in Deductive
Databases
J. Lobo and J. Minker, Univ. of Maryland, USA
From QSQ towards QoSaQ: Global Optimization of Recursive Queries
L. Vieille, ECRC, FR G
Session 10: Panel Session: Knowledge Management
Chairman: Adrian Walker, IBM T.J. Watson Research Center, USA
Panelists: R. Kowalski, Imperial College, London, D. Lenat, MCC,
Austin, Texas, E. Soloway, Yale University and M. Stonebraker, UC -
Berkeley
===================================================================
EDS'88 Tutorial Speaker Bios and Note Contents
Tutorial I
Logic and Databases
Instructor: Dr. Carlo Zaniolo, MCC, Austin, Texas
Dr. Zaniolo heads a group at MCC performing research on deductive
databases and logic programming. He has held positions at Sperry
Research and Bell Laboratories. He is the author of over 40 technical
papers, a member of numerous Program Committees, and edited the
December 1987 Data Engineering special issue on Databases and Logic.
Course Description: There is a growing demand for supporting
knowledge-based applications by means of Knowledge Management Systems;
these will have to combine the inference mechanisms of Logic with the
efficient and secure management of data provided by Database
Management Systems(DBMS). The major topics are: Logic and relational
query languages; Semantics of Horn Clauses; Prolog and DBMSs; Coupling
Prolog with a DBMS; Making Prolog a database language; Integrating
Logic and Database Systems: Sets, Negation and Updates; Choosing an
Execution Model; Compilation: magic sets to support recursive
predicates; Optimization and Safety; Overview of selected R&D
projects.
Tutorial II
Distributed Problem Solving in Knowledge/Data Environments
Instructor: Prof. Victor Lesser, University of Massachusetts, Amherst
Dr. Lesser is Professor of Computer and Information Science at UMASS,
where he heads research groups in Distributed Artificial Intelligence
and Intelligent User Interfaces. Prior to joining UMASS in 1977, he
was on the faculty of Carnegie-Mellon University, where he was a
Principal in the development of the HEARSAY Speech Understanding
System and responsible for the system architecture.
Course Description: This tutorial will explore the major concepts and
systems for cooperative knowledge-based problem solving. The major
topics include: Connectionist, Actor and Cooperating ES paradigms;
Conceptual Issues including: examples of distributed search,
interpretation, planning and cooperation, global coherence, dealing
with inconsistency and incompleteness, sharing world views, and design
rules for a cooperating ES; System Architectures for satisficing,
negotiation, tolerance of inconsistency in problem-solving,
organizational structuring, integration of local and network control,
and expectation-driven communication; Discussion of working systems
including Contract Nets, Partial Global Planning, AGORA MACE, ABE,
DPS, and MINDS.
Tutorial III
Knowledge Representation and Data Semantics
Instructor: Prof. John Mylopoulos, University of Toronto, Canada
Dr. John Mylopoulos is Professor of Computer Science at the University
of Toronto and research fellow of the Canadian Institute for Advanced
Research. His research interests include knowledge representation and
its applications to Databases and Software Engineering. Dr.
Mylopoulos has edited three books on the general topic of AI and
Databases. He received his Ph.D degree from Princeton University.
Course Description: Knowledge Representation including history, basic
paradigms such as semantic nets, logic-based representations,
productions, frames, role of uncertainty, and inference mechanisms,
examples such as KL-ONE and OMEGA; Semantic Data Models including
historical models such as AbrialUs Binary Model, Entity/Relationship,
RM/T and SDM, detailed study of ADAPLEX, TAXIS, and GALILEO,
implementation techniques; Comparison of SDMs to Object-Oriented model
such as POSTGRES and GEM as well as Deductive Databases.
Tutorial IV
Acquisition of Knowledge from Data
Instructor: Prof. Gio Wiederhold, Stanford University, California
Dr. Gio Wiederhold is Associate Professor of Medicine and Computer
Science (Research) at Stanford University. His research involves
knowledge-based approaches to medicine, design, and planning. He is
the Editor-in-Chief of ACM's Transactions on Database Systems and
associate editor of M.D. Computing and IEEE Expert magazine.
Wiederhold has over 130 publications, including a widely used textbook
on Database Design. In 1987, McGraw-Hill published his new book, File
Organization for Database Design.
Course Description: The architecture of an operational system, RX, is
presented which uses knowledge-based techniques to extract new
knowledge from a large clinical database. RX exploits both
frame-based knowledge and rules, as well as a database. Frames are
used to store deep and interconnected knowledge about disease states
and medical actions. Definitional and causal knowledge is
represented by inter-connections between frames that go across the
hierarchies, sideways as well as up and down, so that the aggregate
knowledge is represented by a network. Rules select the appropriate
statistical methods used to reduce the volume of data into
information. The database contains observations on rheumatic
diseases, collected over a dozen years.