Conceptual Database Evolution Through Learning in Object Databases

Qing Li, D. McLeod

Research output: Journal article publicationJournal articleAcademic researchpeer-review

7 Citations (Scopus)

Abstract

Changes to the conceptual structure (meta-data) of a database are common in many application environments and are in general inadequately supported by existing database systems. An approach to supporting such meta-data evolution in a simple, extensible, object database environment is presented. Machine learning techniques are the basis for a cooperative user/system database design and evolution methodology. An experimental end-user database evolution tool based on this approach has been designed and implemented. © 1994 IEEE
Original languageEnglish
Pages (from-to)205-224
Number of pages20
JournalIEEE Transactions on Knowledge and Data Engineering
Volume6
Issue number2
DOIs
Publication statusPublished - 1 Jan 1994
Externally publishedYes

Keywords

  • applied machine learning
  • Conceptual database evolution
  • end-user database tools
  • evolution through learning
  • object databases

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Computational Theory and Mathematics

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