The Development of Genetic Algorithm for Semantic Similarity Estimation in Terms of Knowledge Management Problems

2017 ◽  
pp. 84-93 ◽  
Author(s):  
Yury Kravchenko ◽  
Ilona Kursitys ◽  
Victoria Bova
Keyword(s):  
Genetic Algorithm ◽  
Knowledge Management ◽  
Semantic Similarity ◽  
Similarity Estimation ◽  
Management Problems

Bridging the Gap from the General to the Specific by Linking Knowledge Management to Business Processes

2011 ◽  
pp. 2572-2586
Author(s):  
John S. Edwards ◽  
John B. Kidd
Keyword(s):  
Knowledge Management ◽  
Cultural Change ◽  
Business Processes ◽  
Organisational Learning ◽  
Practical Implementation ◽  
Management Problems ◽  
Potential Benefits ◽  
Almost All ◽  
Different Cultures

A phenomenon common to almost all fields is that there is a gap between theory and practical implementation. However, this is a particular problem in knowledge management, where much of the literature consists of general principles written in the context of a ‘knowledge world’ that has few, if any, references to how to carry out knowledge management in organisations. In this chapter, we put forward the view that the best way to bridge this gap between general principles and the specific issues facing a given organisation is to link knowledge management to the organisation’s business processes. After briefly reviewing, and rejecting alternative ways in which this gap might be bridged, the chapter goes on to explain the justification for, and the potential benefits and snags of, linking knowledge management to business processes. Successful and unsuccessful examples are presented. We concentrate especially on the issues of establishing what knowledge is relevant to an organisation at present, the need for organisational learning to cope with the inevitable change, and the additional problems posed by the growing internationalisation of operations. We conclude that linking knowledge management in terms of business processes is the best route for organisations to follow, but that it is not the answer to all knowledge management problems, especially where different cultures and/or cultural change are involved.

scholarly journals Semantic Similarity Estimation Using Vector Symbolic Architectures

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 109120-109132
Author(s):  
Job Isaias Quiroz-Mercado ◽  
Ricardo Barron-Fernandez ◽  
Marco Antonio Ramirez-Salinas
Keyword(s):  
Semantic Similarity ◽  
Similarity Estimation

Identifying knowledge management problems using a process‐based method (a case study of process 137)

2013 ◽  
Vol 19 (2) ◽  
pp. 263-291 ◽  
Author(s):  
Mina Ranjbarfard ◽  
Mohammad Aghdasi ◽  
Amir Albadvi ◽  
Mohammad Hassanzadeh
Keyword(s):  
Knowledge Management ◽  
Management Problems

Quantity Dimension Indexing for Design Knowledge Management

2007 ◽  
Author(s):  
Tamotsu Murakami ◽  
Yasushi Suehisa
Keyword(s):  
Knowledge Management ◽  
Dimensional Space ◽  
International System ◽  
Design Knowledge ◽  
Design Problems ◽  
Future Design ◽  
Similarity Estimation ◽  
System Of Units ◽  
Physical Phenomena ◽  
Physical Quantities

Although many knowledge management techniques based on text expression have been developed, they are not necessarily sufficient for managing engineering design knowledge. In this paper, we propose quantity dimension indexing of design knowledge as a fundamental method for design knowledge management. Physical quantities describing physical phenomena can be represented as vectors in a seven-dimensional space where the orthogonal axes are the seven base units of the SI (The International System of Units). Because of the generality, objectivity and universality of the SI, this space covers all physical quantities that appear in the past, present and future design knowledge and design problems, and the same quantities are represented as the same vectors regardless of the differences in people, products, domains, organizations, nations and languages. We assume that the similarities of physical phenomena lead to similarities in the dimensions of quantities describing the phenomena, and propose to use this seven-dimensional vector for estimating the similarity of design knowledge from the viewpoint of physical phenomena. Based on this basic idea, we mathematically define similarity between two quantities using quantity dimensions. We prepared design knowledge examples and retrieval keys and conducted design knowledge retrieval and design knowledge similarity estimation by quantity dimension indexing and confirmed that we obtained adequate results without using a concept dictionary or thesaurus elaborated in advance, which are indispensable in the text approach.

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