Design and implementation of an integrated knowledge system

H. C W Lau, Wing Yan Wong, I. K. Hui, K. F. Pun

Research output: Journal article publicationJournal articleAcademic researchpeer-review

42 Citations (Scopus)

Abstract

Case Base Reasoning (CBR), which is characterized by its capability to capture past experience and knowledge for case matching in various applications, is an emerging and well-accepted approach in the implementation Knowledge Management (KM) systems. The data format of CBR belongs to the 'free' type and therefore is dissimilar to the traditional relational data model which emphasizes on specified data fields, field lengths and data types. However, there is a lack of research regarding the seamless integration of these heterogeneous data models for achieving effective data communication, which is essential to enhance business workflow of enterprises. This paper attempts to propose an integrated knowledge system to support the extrapolation of projected outcomes of events based on knowledge generated by the relational database model and CBR knowledge model, both of which supplement and complement each other by virtue of their distinct structural features.
Original languageEnglish
Pages (from-to)69-76
Number of pages8
JournalKnowledge-Based Systems
Volume16
Issue number2
DOIs
Publication statusPublished - 1 Mar 2003

Keywords

  • Case base reasoning
  • Data warehouse
  • Knowledge management
  • Online analytical processing

ASJC Scopus subject areas

  • Artificial Intelligence

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