Continuous improvement of knowledge management systems using Six Sigma methodology

Chiajou Lin, F. Frank Chen, Hung Da Wan, Yuh-Min Chen, Glenn Kuriger

Research output: Contribution to journalArticle

19 Citations (Scopus)

Abstract

Knowledge retrieval is a decisive part of the performance of a knowledge management system. In order to enhance retrieval accuracy, an effective performance evaluation mechanism is necessary. Nowadays, there is not a standard evaluation framework for knowledge retrieval evaluation, because the evaluation set up is still technology-dependent, focusing on specific elements of the search context. The laboratory-based evaluation is not suitable to evaluate the knowledge retrieval process, since knowledge is dynamic, constantly changing and evolving. Besides, ambiguous query is also an important factor for the performance of knowledge retrieval systems. In order to improve the performance of knowledge retrieval, this paper proposes an evaluation mechanism using Six Sigma methodology to help developers continuously control the knowledge retrieval process. Specifically, this study involves the following tasks: (i) proposes a general knowledge retrieval framework based on the analysis result of knowledge retrieval, (ii) designs the knowledge retrieval evaluation framework using Six Sigma's Define-Measure-Analyze-Improve-Control (DMAIC) process and (iii) develops the related technologies to implement the knowledge retrieval evaluation mechanism. The knowledge retrieval evaluation mechanism allows system developers to maintain the knowledge retrieval system with ease and meanwhile enhance the accuracy.

Original languageEnglish
Pages (from-to)95-103
Number of pages9
JournalRobotics and Computer-Integrated Manufacturing
Volume29
Issue number3
DOIs
Publication statusPublished - 2013 Jan 1

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Software
  • Mathematics(all)
  • Computer Science Applications
  • Industrial and Manufacturing Engineering

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