Knowledge representation and processing in relational data base

被引:0
|
作者
Adams, Teresa M. [1 ]
机构
[1] Univ of Wisconsin-Madison, Madison, United States
关键词
Expert systems;
D O I
暂无
中图分类号
学科分类号
摘要
This paper is a comparative study of the set operators in rule-based production languages and relational query languages. This paper illustrates the use of structured query language (SQL) subselect conditions IN, NOT IN, EXISTS, and NOT EXISTS for knowledge processing. The method described in this paper may be effective for expanding existing relational data-base management system applications to knowledge management systems and may reduce the need for algebraic or rule-based programming to embed expertise. As an example, a set of knowledge tables that contain the relationships between in-situ soil improvement techniques, relative cost, soil types, engineering properties, and the benefits and limitations of these improvement techniques are described. The operations for manipulating the tables to select and rank soil improvement techniques are written as SQL queries. The queries are compared to a set of expert system language rules that will accomplish the task. The results indicate the potential use of engineering knowledge tables for developing design aids. Forms of the queries described in this paper can be used by practitioners, data-base developers and expert system programmers to expand the potential use of new and existing data bases.
引用
收藏
页码:238 / 255
相关论文
共 50 条
  • [41] Nested Subspace Arrangement for Representation of Relational Data
    Hata, Nozomi
    Kaji, Shizuo
    Yoshida, Akihiro
    Fujisawa, Katsuki
    INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 119, 2020, 119
  • [42] INDETERMINACY IN A SYSTEM FOR KNOWLEDGE REPRESENTATION AND PROCESSING
    NARINYANI, AS
    SOVIET JOURNAL OF COMPUTER AND SYSTEMS SCIENCES, 1987, 25 (02): : 49 - 69
  • [43] FEATS - KNOWLEDGE REPRESENTATION AND PROCESSING ISSUES
    BYKAT, A
    KNOWLEDGE-BASED SYSTEMS, 1993, 6 (03) : 157 - 164
  • [44] A Data-Driven Approach to Infer Knowledge Base Representation for Natural Language Relations
    Luo, Kangqi
    Luo, Xusheng
    Chen, Xianyang
    Zhu, Kenny Q.
    PROCEEDINGS OF THE TWENTY-SIXTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2017, : 1174 - 1180
  • [45] RELATIONAL DATA BASE SYSTEM RIQS (RELATIONAL INFORMATION QUERY SYSTEM).
    Hara, Kazuyuki
    Miyazaki, Thuyoshi
    Nishi, Tatsumi
    Iwamoto, Kazuma
    Ideshita, Tadayoshi
    1600,
  • [46] ON BUBBLE MEMORIES AND RELATIONAL DATA BASE.
    Chang, H.
    1978, : 207 - 242
  • [47] A PRIMER ON RELATIONAL DATA-BASE CONCEPTS
    SANDBERG, G
    IBM SYSTEMS JOURNAL, 1981, 20 (01) : 23 - 40
  • [48] NAVIGATIONAL FACILITIES FOR RELATIONAL DATA-BASE
    SUBIETA, K
    INFORMATION SYSTEMS, 1983, 8 (01) : 29 - 36
  • [49] RDBM - A RELATIONAL DATA-BASE MACHINE
    AUER, H
    HELL, W
    LEILICH, HO
    LIE, JS
    SCHWEPPE, H
    SEEHUSEN, S
    STIEGE, G
    TEICH, W
    ZEIDLER, HC
    INFORMATION SYSTEMS, 1981, 6 (02) : 91 - 100
  • [50] RELATIONAL PASCAL DATA-BASE INTERFACE
    ALAGIC, S
    KULENOVIC, A
    COMPUTER JOURNAL, 1981, 24 (02): : 112 - 117