Capability Maturity

2011 ◽  
pp. 24-29 ◽  
Author(s):  
Alfs T. Berztiss
Keyword(s):  
Data Mining ◽  
Knowledge Management ◽  
Knowledge Representation ◽  
Organizational Structure ◽  
Knowledge Engineering ◽  
Rapid Change ◽  
Insurance Company ◽  
Capability Maturity ◽  
Recent Origin ◽  
To Come

The dependence of any organization on knowledge management is clearly understood. Actually, we should distinguish between knowledge management (KM) and knowledge engineering (KE): KM is to define and support organizational structure, allocate personnel to tasks, and monitor knowledge engineering activities; KE is concerned with technical matters, such as tools for knowledge acquisition, knowledge representation, and data mining. We shall use the designation KMKE for knowledge management and knowledge engineering collectively. KM is a very young area—the three articles termed “classic works” in Morey, Maybury, and Thuraisingham (2000) date from 1990, 1995, and 1996, respectively. We could regard 1991 as the start of institutionalized KM. This is when the Skandia AFS insurance company appointed a director of intellectual capital. KE has a longer history—expert systems have been in place for many years. Because of its recent origin, KMKE is characterized by rapid change. To deal with the change, we need to come to a good understanding of the nature of KMKE.

Capability Maturity

2011 ◽  
pp. 1117-1124
Author(s):  
Alfs T. Berztiss
Keyword(s):  
Data Mining ◽  
Knowledge Management ◽  
Knowledge Representation ◽  
Organizational Structure ◽  
Knowledge Engineering ◽  
Rapid Change ◽  
Insurance Company ◽  
Capability Maturity ◽  
Recent Origin ◽  
To Come

The dependence of any organization on knowledge management is clearly understood. Actually, we should distinguish between knowledge management (KM) and knowledge engineering (KE): KM is to define and support organizational structure, allocate personnel to tasks, and monitor knowledge engineering activities; KE is concerned with technical matters, such as tools for knowledge acquisition, knowledge representation, and data mining. We shall use the designation KMKE for knowledge management and knowledge engineering collectively. KM is a very young area—the three articles termed “classic works” in Morey, Maybury, and Thuraisingham (2000) date from 1990, 1995, and 1996, respectively. We could regard 1991 as the start of institutionalized KM. This is when the Skandia AFS insurance company appointed a director of intellectual capital. KE has a longer history—expert systems have been in place for many years. Because of its recent origin, KMKE is characterized by rapid change. To deal with the change, we need to come to a good understanding of the nature of KMKE.

Capability Maturity

2011 ◽  
pp. 81-88
Author(s):  
Alfs T. Berztiss
Keyword(s):  
Data Mining ◽  
Knowledge Management ◽  
Knowledge Representation ◽  
Organizational Structure ◽  
Knowledge Engineering ◽  
Rapid Change ◽  
Insurance Company ◽  
Capability Maturity ◽  
Recent Origin ◽  
To Come

The dependence of any organization on knowledge management is clearly understood. Actually, we should distinguish between knowledge management (KM) and knowledge engineering (KE): KM is to define and support organizational structure, allocate personnel to tasks, and monitor knowledge engineering activities; KE is concerned with technical matters, such as tools for knowledge acquisition, knowledge representation, and data mining. We shall use the designation KMKE for knowledge management and knowledge engineering collectively. KM is a very young area—the three articles termed “classic works” in Morey, Maybury, and Thuraisingham (2000) date from 1990, 1995, and 1996, respectively. We could regard 1991 as the start of institutionalized KM. This is when the Skandia AFS insurance company appointed a director of intellectual capital. KE has a longer history—expert systems have been in place for many years. Because of its recent origin, KMKE is characterized by rapid change. To deal with the change, we need to come to a good understanding of the nature of KMKE.

Formal Knowledge Engineering Methods for Knowledge Discovery

2002 ◽  
Vol 01 (02) ◽  
pp. 141-154
Author(s):  
Satheesh Ramachandran
Keyword(s):  
Data Mining ◽  
Knowledge Management ◽  
Life Cycle ◽  
Decision Support ◽  
Knowledge Discovery ◽  
Knowledge Engineering ◽  
The Other ◽  
Full Potential ◽  
Formal Knowledge

This paper presents a framework for the integrated use of formal knowledge engineering methods and data mining based knowledge discovery methods. Knowledge is a key enterprise asset, and organizations are adopting both knowledge engineering and knowledge discovery paradigms for better knowledge management and enhanced decision support capability. Although there exists a useful interdependence between these endeavors, not much effort has been focused on using the full potential of one for the other. This paper presents a framework for the integrated use of established formal knowledge engineering methods and knowledge discovery processes with the ultimate intent of better managing the enterprise knowledge life cycle. It provides a brief overview of the knowledge discovery processes, and introduces a class of formal knowledge engineering methods and the perceived role of these methods in supporting the integration between the two worlds of knowledge discovery and knowledge engineering.

scholarly journals Intelligent Class Scheduler in Kathmandu University

2018 ◽  
Vol 10 (4) ◽  
pp. 17
Author(s):  
Gajendra Sharma Rabin Shrestha
Keyword(s):  
Knowledge Management ◽  
Exchange Of Information ◽  
Class Schedule ◽  
Lecture Room ◽  
Class Scheduling ◽  
To Come ◽  
The University ◽  
Knowledge Portal

Imagine the University where everything runs smoothly, there is no need to worry about information that needs to be known where the University shares all information in your ear. Imagine that you know every location of your University and the schedules are relevant. This research focuses on the problem faced by Kathmandu University (KU) students while searching for their lecture room and managing their class schedule. This research is carried out for proposing knowledge portal for an intelligent class scheduling and location directing on the central campus of KU. The quest of the information world to make everyday easier has driven us to come up with the concept of such an app and this research consists of role of knowledge management for the development of an application by sharing and exchange of information between individuals and the administration. The university will be benefited in at least a small way through the paper.

scholarly journals Collaborative Robots and Knowledge Management - A Short Review

2017 ◽  
Vol 69 (1) ◽  
pp. 143-147 ◽  
Author(s):  
Flaviu-Constantin Mușat ◽  
Florin-Constantin Mihu
Keyword(s):  
Knowledge Management ◽  
Management System ◽  
Short Review ◽  
Knowledge Management System ◽  
Work Place ◽  
Collaborative Robots ◽  
Delivery Times ◽  
Parallel Tasks ◽  
To Come ◽  
Automated Lines

Abstract Because the requirements of the customers are more and more high related to quality, quantity, delivery times at lowest costs possible, the industry had to come with automated solutions to improve these requirements. Starting from the automated lines developed by Ford and Toyota, we have now developed automated and self-sustained working lines, which is possible nowadays-using collaborative robots. By using the knowledge management system we can improve the development of the future of this kind of area of research. This paper shows the benefits and the smartness use of the robots that are performing the manipulation activities that increases the work place ergonomically and improve the interaction between human - machine in order to assist in parallel tasks and lowering the physically human efforts.

Association between mass collaboration and knowledge management: a case ofJordan companies

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hosam Alden Riyadh ◽  
Laith T. Khrais ◽  
Salsabila Aisyah Alfaiza ◽  
Abdulsatar Abduljabbar Sultan
Keyword(s):  
Knowledge Management ◽  
Organizational Structure ◽  
Structural Equation ◽  
Manufacturing Sector ◽  
Equation Modeling ◽  
Content Type ◽  
Mass Collaboration ◽  
Organization Level ◽  
Learning Techniques ◽  
The Impact

Purpose The key purpose of this research paper was to identify the association between mass collaboration and knowledge management in the context of Jordanian companies. Apart from that, this study also aims to examine the moderating effect of trust and leadership on the association between mass collaboration and knowledge management. Design/methodology/approach In this study, the researcher has followed theprimary quantitative method. For data collection, the researcher has conducted a survey questionnaire, whereas the sample was based on 323 participants from the manufacturing sector of Jordan specifically for data analysis; the technique of structural equation modeling was implemented. Findings All the independent variables, including organizational structure, adoptedtechnologies in mass collaboration and collaborative learning techniques, have a significantimpact on knowledge management and leadership. Moreover, leadership was also found to be significantly moderating the association between adopted technologies in mass collaboration and knowledge management. Similarly, trust also significantly moderates the association of organizational structure and adopted technologies in mass collaboration significantly with knowledge management. Research limitations/implications All study respondents were from Jordan, which might limit the generalizability of the findings. The researchers also invited for more researchers in the incorporation of the time sequence in the proposed causal relations and in the organization level through which mass collaboration and knowledge management. Originality/value This study promises to make a valuable contribution to the existing literature, as there was a lack of evidence in the previous studies regarding the impact of mass collaboration on knowledge management within the context of Jordan.

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