首页    期刊浏览 2025年02月22日 星期六
登录注册

文章基本信息

  • 标题:The Knowledge Repository Management System Architecture of Digital Knowledge Engineering using Machine Learning to Promote Software Engineering Competencies
  • 本地全文:下载
  • 作者:Nattaphol Thanachawengsakul ; Panita Wannapiroon ; Prachyanun Nilsook
  • 期刊名称:International Journal of Emerging Technologies in Learning (iJET)
  • 印刷版ISSN:1863-0383
  • 出版年度:2019
  • 卷号:14
  • 期号:12
  • 页码:42-56
  • DOI:10.3991/ijet.v14i12.10444
  • 出版社:Kassel University Press
  • 摘要:The knowledge repository management system architecture of digital knowledge engineering using machine learning (KRMS-SWE) to promote software engineering competencies is comprised of four parts, as follows: 1) device service, 2) application service, 3) module service of the KRMS-SWE and 4) machine learning service and storage unit. The knowledge creation, storage, testing and assessing of students’ knowledge in software engineering is carried out using a knowledge verification process with machine learning and divided into six steps, as follows: pre-processing, filtration, stemming, indexing, data mining and interpretation and evaluation. The overall result regarding the suitability of the KRMS-SWE is assessed by five experts who have high levels of experience in related fields. The findings reveal that this research approach can be applied to the future development of the KRMS-SWE.
  • 关键词:System Architecture; KRMS-SWE; Digital Knowledge Engineering; Machine Learning
国家哲学社会科学文献中心版权所有