• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.50-52
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• 2009

Ontology maintenance is a time consuming and costly process which requires special skill and knowledge. It requires joint effort of both ontology engineer and domain specialist to properly maintain ontology and update knowledge in it. This is specially true for medical domain which is highly specialized domain. This paper proposes a novel approach for maintenance and update of existing ontologies in a medical domain. The proposed approach is based on modified Ontology Maturing Process which was originally developed for web domain. The proposed approach provides way to populate medical ontology with new knowledge obtained from medical documents. This is achieved through use of natural language processing techniques and highly specialized medical knowledge bases such as Unified Medical Language System.

• Journal of Korea Multimedia Society
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• v.25 no.6
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• pp.819-832
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• 2022

Cross-domain recommender system transfers knowledge across different domains to improve the recommendation performance in a target domain that has a relatively sparse model. However, they suffer from the "negative transfer" in which transferred knowledge operates as noise. This paper proposes a novel Multiple Fusion-based Deep Cross-Domain Recommendation named MFDCR. We exploit Doc2Vec, one of the famous word embedding techniques, to fuse data user-wise and transfer knowledge across multi-domains. It alleviates the "negative transfer" problem. Additionally, we introduce a simple multi-layer perception to learn the user-item interactions and predict the possibility of preferring items by users. Extensive experiments with three domain datasets from one of the most famous services Amazon demonstrate that MFDCR outperforms recent single and cross-domain recommendation algorithms. Furthermore, experimental results show that MFDCR can address the problem of "negative transfer" and improve recommendation performance for multiple domains simultaneously. In addition, we show that our approach is efficient in extending toward more domains.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.3 s.180
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• pp.22-31
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• 2006

This paper introduces an approach to an ontology-based knowledge framework for product life cycle management (PLM). Participants in a product life cycle want to share comprehensive product knowledge without any ambiguity and heterogeneity. However, previous knowledge management approaches are limited in providing those aspects. Therefore, we suggest an ontology-based knowledge framework including knowledge maps, axioms and specific knowledge far domain. The bottom level, the axiom, specifies the semantics of concepts and relations of knowledge so that ambiguity of the semantics can be alleviated. The middle level is a product development knowledge map; it defines the concepts and the relations of the product domain common knowledge and guides engineers to process their engineering decisions. The middle level is then classified further into more detailed levels, such as generic product level, specific product level, product version level, and product item level for PLM. The top level is specialized knowledge fer a specific domain that gives the solution of a specific task or problem. It is classified into three knowledge types: expert knowledge, engineering function knowledge, and data-analysis-based knowledge. This proposed framework is based on ontology to accommodate a comprehensive range of unambiguous knowledge for PLM and is represented with first-order logic to maintain a uniform representation.

• Journal of Information Processing Systems
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• v.13 no.1
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• pp.57-67
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• 2017

In this paper, Atanassov's intuitionistic fuzzy set theory is used to handle the uncertainty of students' knowledgeon domain concepts in an E-learning system. Their knowledge on these domain concepts has been collected from tests that were conducted during their learning phase. Atanassov's intuitionistic fuzzy user model is proposed to deal with vagueness in the user's knowledge description in domain concepts. The user model uses Atanassov's intuitionistic fuzzy sets for knowledge representation and linguistic rules for updating the user model. The scores obtained by each student were collected in this model and the decision about the students' knowledge acquisition for each concept whether completely learned, completely known, partially known or completely unknown were placed into the information table. Finally, it has been found that the proposed scheme is more appropriate than the fuzzy scheme.

• Journal of Korean Biological Nursing Science
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• v.18 no.3
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• pp.160-168
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• 2016

Purpose: This study was conducted to examine the pro-environmental attitude (actual commitment domain, verbal commitment domain, affect domain), behavior to decreased exposure and knowledge of endocrine disruptors by obesity -related profiles (BMI, body fat percentage, visceral fat percentage, skeletal muscle mass percentage, waist circumference, waist-hip ratio). Methods: A cross-sectional study was conducted with 102 nursing students. Data were collected from November to December, 2015 using self-report questionnaires and physical measurements. Data were analyzed using t-test, Pearson correlation and coefficients with SPSS 18.0. Results: The study results showed that actual commitment domain of pro-environmental attitude and behavior to decreased exposure level on endocrine disruptors were significantly related to visceral fat percentage. Actual commitment domain of a pro-environmental attitude was significantly related to body fat percentage. Pro-environmental attitude was significantly related to the behavior to decreased exposure level on endocrine disruptors and knowledge thereof. Conclusion: These findings suggest that visceral fat and body fat percentages were significantly related to the actual commitment domain of a pro-environmental attitude. Therefore, a replication study is recommended to understand the connection between endocrine disruptors and obesity. In addition, developing an education program about endocrine disruptors for nursing students is recommended. In particular, a pro-environmental attitude, especially on actual commitment domain, could be involved as an education program.

• Journal of the Korean Society for Library and Information Science
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• v.39 no.4
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• pp.89-104
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• 2005

This article identifies an emerging research paradigm and monitors the changes in digital preservation area using CiteSpace, a Java application which supports visual exploration with knowledge discovery in bibliographic databases. 74 articles on digital preservation field covering the time period from 1990-2005 were extracted from Web of Science. According to the result of analysis, core knowledge domains in digital preservation are technical preservation strategies, information network and preservation system, knowledge management and electronic government.

• Journal of the Korean Applied Science and Technology
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• v.39 no.6
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• pp.738-747
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• 2022

The purpose of this study is to construct a knowledge structure for the application of physical education in ecological marine sports. As specific exercises, a volleyball game (beach volleyball) and open water swimming were set, and a knowledge structure analysis framework was used for the study. Expert consultation was conducted to secure the validity of the study. The study results are as follows. First, a knowledge structure based on the 2022 revised physical education curriculum was prepared. Second, the basis for the application of physical education classes for ecological marine sports was prepared. Third, learning contents in the knowledge·understanding domain, process·functional domain, and value·attitude domain of beach volleyball were proposed. Fourth, learning contents of knowledge·understanding domain, process·function domain, and value·attitude domain of sea swimming were proposed. This study is meaningful in that it prepared in advance for the realization of the 2022 revised physical education curriculum to be introduced in the future.

• Knowledge Management Research
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• v.6 no.2
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• pp.23-47
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• 2005

This study is performed the multinomial logistic regression with the officials needs level about a component of knowledge administration for drawing a demand estimation model in the knowledge administration activities. This study is not that an activity and domain of knowledge administration is to apply and to operate uniformly it in public sector, one is suggested an application with a demand diagnose of knowledge administration in order to saw a course of the knowledge administration programs to suit a function and role of public administration. A result of this study is that an activity and domain of the knowledge administration is different from a component of it namely, knowledge creating, knowledge organizing, knowledge sharing and distribution, knowledge utility, and knowledge store. And the officials individual characteristics, administration agency, a kind of business, and a function and role of work are different from demand of knowledge administration. Also, the practical use of KMS (knowledge management system) is not so high in public sector. Accordingly, the tools of knowledge administration will deliberate on a consolidation with the existing system in the device.

• Journal of the Korea Safety Management & Science
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• v.15 no.3
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• pp.133-141
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• 2013

As a work analysis technique, Work Domain Analysis (WDA) aims to identify the design knowledge structure of a work domain that human operators interact with through human-system interfaces. Abstraction hierarchy (AH) is a multi-level, hierarchical knowledge representation framework for modeling the functional structure of any kinds of systems. Thus, WDA based on AH aims to identify the functional knowledge structure of a work domain. AH has been used in a range of work domains and problems to model their functional knowledge structure and has proven its generality and usefulness. However, many of researchers and system designers have reported that it is never easy to understand the concepts underlying AH and use it effectively for WDA. This would be because WDA is a form of work analysis that is different from other types of work analysis techniques such as task analysis and AH has several unique characteristics that are differentiated from other types of function analysis techniques used in systems engineering. With this issue in mind, this paper introduces the concepts of WDA based on AH and offers a comprehensive list of references. Next, this paper proposes a set of principles for effectively applying AH for work domain analysis, which are developed based on the author's experiences, consultation with experts, and literature reviews.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.173.5-173
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• 2001

Q-Learning is a most widely used reinforcement learning, which addresses the question of how an autonomous agent can learn to choose optimal actions to achieve its goal about any one problem. Q-Learning can acquire optimal control strategies from delayed rewards, even when the agent has no prior knowledge of the effects of its action in the environment. If agent has an ability using previous knowledge, then it is expected that the agent can speed up learning by interacting with environment. We present a novel reinforcement learning method using domain knowledge, which is represented by problem-independent features and their classifiers. Here neural network are implied as knowledge classifiers. To show that an agent using domain knowledge can have better performance than the agent with standard Q-Learner. Computer simulations are ...