scholarly journals Synthesis of Digital Knowledge Engineering Repository Management System

2019 ◽  
Vol 9 (4) ◽  
pp. 348-356
Author(s):  
Nattaphol Thanachawengsakul ◽  
◽  
Panita Wannapiroon ◽  
Prachyanun Nilsook
Keyword(s):  
Management System ◽  
Knowledge Engineering ◽  
Digital Knowledge

scholarly journals The Knowledge Repository Management System Architecture of Digital Knowledge Engineering using Machine Learning to Promote Software Engineering Competencies

2019 ◽  
Vol 14 (12) ◽  
pp. 42 ◽  
Author(s):  
Nattaphol Thanachawengsakul ◽  
Panita Wannapiroon ◽  
Prachyanun Nilsook
Keyword(s):  
Machine Learning ◽  
Software Engineering ◽  
System Architecture ◽  
Management System ◽  
Knowledge Engineering ◽  
Research Approach ◽  
Storage Unit ◽  
Knowledge Repository ◽  
Application Service ◽  
Digital Knowledge

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.

scholarly journals The Development of a MOOCs Knowledge Repository System Using a Digital Knowledge Engineering Process to Enhance Digital Entrepreneurs’ Competencies

2021 ◽  
Vol 11 (6) ◽  
pp. 85-101
Author(s):  
Nattaphol Thanachawengsakul ◽  
Panita Wannapiroon
Keyword(s):  
Human Performance ◽  
Knowledge Engineering ◽  
Small And Medium Enterprises ◽  
Competency Assessment ◽  
Engineering Process ◽  
Significance Level ◽  
Knowledge Repository ◽  
Digital Knowledge ◽  
Dependent Sample ◽  
Medium Enterprises

The objectives of this research were as follows: the development of a MOOCs knowledge repository system using a digital knowledge engineering process, and a competency assessment of digital entrepreneurs engaging in a MOOCs knowledge repository system using a digital knowledge engineering process. A total of 30 people were selected as a sampling group (purposive sampling) for this study, these included Small and Medium Enterprises (SMEs) in Bangkok with expertise in Human Performance Technology (HPT), as well as the MOOCs knowledge repository system. The mean, standard deviation, percentage, and a dependent sample t-test were used in the procedure for data analysis. The research findings suggested that: (1) the overall result concerning the development of a MOOCs knowledge repository system using a digital knowledge engineering process was at the highest level (Mean = 4.89, S.D. = 0.31), and (2) the overall result regarding the competencies of digital entrepreneurs after engaging in a MOOCs knowledge repository system using a digital knowledge engineering process passed the 80% rating, according to criteria. Moreover, learners who had undertaken activities through a MOOCs knowledge repository system using a digital knowledge engineering process improved their learning outcomes with a significance level of .05 based on the research hypothesis.

Metrics for Concept-Oriented Knowledge Bases

1998 ◽  
Vol 08 (02) ◽  
pp. 161-188 ◽  
Author(s):  
Timothy C. Lethbridge
Keyword(s):  
Knowledge Management ◽  
Software Engineering ◽  
Knowledge Base ◽  
Management System ◽  
Software Metrics ◽  
Knowledge Engineering ◽  
Knowledge Bases ◽  
Knowledge Management System ◽  
The Other ◽  
Develop Software

Metrics are widely researched and used in software engineering; however there is little analogous work in the field of knowledge engineering. In other words, there are no widely-known metrics that the developers of knowledge bases can use to monitor and improve their work. In this paper we adapt the GQM (Goals-Questions-Metrics) methodology that is used to select and develop software metrics. We use the methodology to develop a series of metrics that measure the size and complexity of concept-oriented knowledge bases. Two of the metrics measure raw size; seven measure various aspects of complexity on scales of 0 to 1, and are shown to be largely independent of each other. The remaining three are compound metrics that combine aspects of the other nine in an attempt to measure the overall 'difficulty' or 'complexity' of a knowledge base. The metrics have been implemented and tested in the context of a knowledge management system called CODE4.

Application of Web Based Knowledge Management System in University Libraries

2013 ◽  
Vol 336-338 ◽  
pp. 2572-2576
Author(s):  
Du Jing ◽  
Xiang Rong Gao ◽  
Yong Cui Yuan
Keyword(s):  
Knowledge Management ◽  
Management System ◽  
Knowledge Management System ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
University Libraries ◽  
Model Framework ◽  
Web Based ◽  
Library Users ◽  
Digital Knowledge

Web based knowledge management systems have opened new arrays in the present web based world. This paper proposed a web based knowledge management system (WBKMS) for university libraries that will support the creation, organization, storage, dissemination and utilization of the institutions digital knowledge assets. Existing web based knowledge management systems were surveyed and a model framework was developed keeping in view the prevailing loopholes in the present systems. This research will improve staff professionalism and will help in achieving coordination with other libraries and library users.

scholarly journals The Effectiveness of “Knowledge Management System” in Research Mentoring Using Knowledge Engineering

2014 ◽  
Vol 7 (5) ◽  
Author(s):  
Puangpet Sriwichai ◽  
Komsak Meksamoot ◽  
Nopasit Chakpitak ◽  
Keshav Dahal ◽  
Anchalee Jengjalean
Keyword(s):  
Knowledge Management ◽  
Management System ◽  
Knowledge Engineering ◽  
Knowledge Management System ◽  
Research Mentoring
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