How Does an Expert System Get its Data? (Extended Abstract).

Yannis Vassiliou, James Clifford, Matthias Jarke: How Does an Expert System Get its Data? (Extended Abstract). VLDB 1983: 70-72
  author    = {Yannis Vassiliou and
               James Clifford and
               Matthias Jarke},
  editor    = {Mario Schkolnick and
               Costantino Thanos},
  title     = {How Does an Expert System Get its Data? (Extended Abstract)},
  booktitle = {9th International Conference on Very Large Data Bases, October
               31 - November 2, 1983, Florence, Italy, Proceedings},
  publisher = {Morgan Kaufmann},
  year      = {1983},
  isbn      = {0-934613-15-X},
  pages     = {70-72},
  ee        = {db/conf/vldb/VassiliouCJ83.html},
  crossref  = {DBLP:conf/vldb/83},
  bibsource = {DBLP,}


An Expert System (Es) is a problem-solving computer system that incorporates enough knowledge in somne specialized problem domain to reach a level of performance comparable to that of a human expert. In the heart of an expert system lies the program that "reasons" and makes deductions ("inference engine"). To reason, knowledge both of general rules (e.g. if a person works for a company then he/she gets employee benefits) and of specific declarative facts (e.g. john works for nyu) is needed. With few exceptions, little attention is given in ESs to the handling of very large populations Of specific facts. Since early prototype ESs represented specific facts which were characterized by large variety and a very small population, the inefficiency of data handling was not an issue. As ESs increase in sophistication and ambition, they deal with applications requiring a very large population of facts, often in the form of existing databases manipulated by generalized DBMS. This short paper (see Vassiliou et al 1983 for more details) investigates the technical issues of enhancing expert systems with database management facilities in four stages, leading to the coupling of the ES with a large DBMS. Our vehicles are first-order logic (with Prolog) and relational database management.

Copyright © 1983 by the VLDB Endowment. Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the VLDB copyright notice and the title of the publication and its date appear, and notice is given that copying is by the permission of the Very Large Data Base Endowment. To copy otherwise, or to republish, requires a fee and/or special permission from the Endowment.

Online Paper

ACM SIGMOD Anthology

CDROM Version: Load the CDROM "Volume 1 Issue 4, VLDB '75-'88" and ... DVD Version: Load ACM SIGMOD Anthology DVD 1" and ...

Printed Edition

Mario Schkolnick, Costantino Thanos (Eds.): 9th International Conference on Very Large Data Bases, October 31 - November 2, 1983, Florence, Italy, Proceedings. Morgan Kaufmann 1983, ISBN 0-934613-15-X
Contents CiteSeerX Google scholar BibTeX bibliographical record in XML



Copyright © Sun Mar 14 23:30:06 2010 by Michael Ley (