Skill‐based education through fuzzy knowledge modeling for e‐learning

Skill‐based education through fuzzy knowledge modeling for e‐learning INTRODUCTIONKnowledge retrieval is a process of extracting information from structured data. Nowadays knowledge capturing, knowledge transformation, knowledge deployment, and knowledge recycling are the emerging areas of organizational development. The most significant point of development is improving the skill in different fields of the technical staff (professionals), engineers, learner community, and teaching faculties. In real word scenario, the following methods are adapted to achieve excellent results of development and evolution of an organization. This has been achieved through continues training like tutoring, hands‐on training, in‐plant training, etc.The reason for using fuzzy logic is that it does not need lots of data to train and it has interpreted skill and simplicity. Hence, it is used to “compute with words” . In information retrieval system, the search engines are very effective to find relevant learning material in web pages, when new rules are added.The following sections illustrate the related work, fuzzy‐based knowledge representation, fuzzy logic rule for skill‐based learning, and examples of system operation.RELATED WORKAn ontology‐based knowledge retrieval framework [21,25] is proposed to discover a user's background knowledge. Knowledge retrieval model provides various strategies like (a) Information resource retrieval; (b) Retrieval on the knowledge base; (c) Retrieval on concept knowledge base; (d) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Computer Applications in Engineering Education Wiley

Skill‐based education through fuzzy knowledge modeling for e‐learning

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Publisher
Wiley Subscription Services, Inc., A Wiley Company
Copyright
© 2018 Wiley Periodicals, Inc.
ISSN
1061-3773
eISSN
1099-0542
D.O.I.
10.1002/cae.21892
Publisher site
See Article on Publisher Site

Abstract

INTRODUCTIONKnowledge retrieval is a process of extracting information from structured data. Nowadays knowledge capturing, knowledge transformation, knowledge deployment, and knowledge recycling are the emerging areas of organizational development. The most significant point of development is improving the skill in different fields of the technical staff (professionals), engineers, learner community, and teaching faculties. In real word scenario, the following methods are adapted to achieve excellent results of development and evolution of an organization. This has been achieved through continues training like tutoring, hands‐on training, in‐plant training, etc.The reason for using fuzzy logic is that it does not need lots of data to train and it has interpreted skill and simplicity. Hence, it is used to “compute with words” . In information retrieval system, the search engines are very effective to find relevant learning material in web pages, when new rules are added.The following sections illustrate the related work, fuzzy‐based knowledge representation, fuzzy logic rule for skill‐based learning, and examples of system operation.RELATED WORKAn ontology‐based knowledge retrieval framework [21,25] is proposed to discover a user's background knowledge. Knowledge retrieval model provides various strategies like (a) Information resource retrieval; (b) Retrieval on the knowledge base; (c) Retrieval on concept knowledge base; (d)

Journal

Computer Applications in Engineering EducationWiley

Published: Jan 1, 2018

Keywords: ; ; ; ;

References

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