• The Journal of Korean Association of Computer Education
• /
• v.13 no.1
• /
• pp.65-73
• /
• 2010

This study offered lexical knowledge acquisition model of unsupervised learning method in order to overcome limitation of lexical knowledge hand building manual of supervised learning method for research of natural language processing. The offered model obtains the lexical knowledge from the lexical entry which was given by inputting through the process of vectorization, clustering, lexical knowledge acquisition automatically. In the process of obtaining the lexical knowledge acquisition of model, some parts of lexical knowledge dictionary which changes in the number of lexical knowledge and characteristics of lexical knowledge appeared by parameter changes were shown. The experimental results show that is possibility of automatic building of Machine-readable dictionary, because observed to the number of lexical class information cluster collected constant. also building of lexical ditionary including left-morphosyntactic information and right-morphosyntactic information is reflected korean characteristic.

• Proceedings of the KIEE Conference
• /
• 1988.07a
• /
• pp.506-509
• /
• 1988

This paper describes an effective knowledge acquisition method in the fault diagnosis expert system for the electronic switching system TDX-1A. The knowledge acquisition procedure consists of the knowledge collection, the fault diagnosis modeling and the knowledge representation. Furthermore, to improve the performance of the knowledge bases with rule and frame representation, we showed the knowledge base checking methodlogy by using redundancy and inconsistency check algorithm.

• Journal of Korea Technology Innovation Society
• /
• v.9 no.4
• /
• pp.884-908
• /
• 2006

The focus of this study is to analyze the link between existing knowledge in the organization and NPD performance. After a comprehensive literature review, we identified factors influential in the management of existing knowledge, such as efficiency of information acquisition, shared interpretation, structure of organization. Through an empirical research, we found that existing knowledge was positively associated with the efficiency of information acquisition and shared interpretation. Additionally, a strong relationship was found between information acquisition efficiency and NPD. Shared information, however, was not found to be associated with NPD. This result, make us recognize the necessity to better understand some subprocesses through which existing knowledge affects new product performance.

• Journal of Information Science Theory and Practice
• /
• v.10 no.3
• /
• pp.24-39
• /
• 2022

Online learning is becoming ubiquitous worldwide because of its accessibility anytime and from anywhere. However, it cannot be successfully implemented without understanding constructs that may affect its adoption. Unlike previous literature, this research extends the Unified Theory of Acceptance and Use of Technology with three well-known theories, namely compatibility, online self-efficacy, and knowledge sharing and acquisition to examine online learning adoption. A total of 264 higher education students took part in this research. Partial Least Squares-Structural Equation Modeling was used to evaluate the proposed theoretical model. The findings suggested that performance expectancy and compatibility were significant predictors of behavioral intention, whereas behavioral intention, facilitating conditions, and compatibility had a significant and direct effect on online learning's actual use. The results also showed that knowledge acquisition, knowledge sharing, and online self-efficacy were determinates of performance expectancy. Finally, online self-efficacy was a predictor of effort expectancy. The proposed model achieved a high fit and explained 47.7%, 75.1%, 76.1%, and 71.8% of the variance of effort expectancy, performance expectancy, behavioral intention, and online learning actual use, respectively. This study has many theoretical and practical implications that have been discussed for further research.

• Journal of Intelligence and Information Systems
• /
• v.1 no.2
• /
• pp.123-137
• /
• 1995

Most of solution methods in scheduling attempt to generate good solutions by either developing algorithms or heuristic rules. However, scheduling problems in the real world require considering more factors such as multiple objectives, different combinations of heuristic rules due to problem characteristics. In this respect, the traditional mathematical a, pp.oach showed limited performance so that new a, pp.oaches need to be developed. Expert system is one of them. When an expert system is developed for scheduling one of the most difficult processes faced could be knowledge acquisition on scheduling heuristics. In this paper we propose a method for the acquisition of knowledge on the selection of scheduling heuristics using Dempster-Shafer Theory(DST). We also show the examples in the multi-objectives environment.

• The Journal of Society for e-Business Studies
• /
• v.21 no.1
• /
• pp.79-90
• /
• 2016

Autonomous knowledge service, a fully-automated and pervasive service for knowledge acquisition and support based on the power of recent ITs is gaining tremendous interest more and more, as not only the level of users' intelligence increases but also the maturity of IT infrastructure improves. Conventional approaches of knowledge service, however, could not satisfy users because they usually provided undesired knowledge which had been acquired without considering users' want. In other words, knowledge acquisition and distribution were separately performed. This research, therefore, suggests an amended autonomous knowledge service framework by fully-automating the whole phases of knowledge life cycle, from knowledge acquisition to distribution. ASKs, the prototype system of this research, is also implemented by defining and specifying component technologies which constituently compose suggested framework. More user-friendly and applicable way of knowledge service will be derived and facilitated through this research.

• Journal of Intelligence and Information Systems
• /
• v.2 no.2
• /
• pp.69-83
• /
• 1996

The objective of this research is to develop a knowledge acquisition and refinement method for a multi-objective and multi-decision FMS scheduling problem. A competitive neural network and an inductive learning algorithm are integrated to extract and refine necessary scheduling knowledge from simulation outputs. The obtained scheduling knowledge can assist the FMS operator in real-time to decide multiple decisions simultaneously, while maximally meeting multiple objective desired by the FMS operator. The acquired scheduling knowledge for an FMS scheduling problem is tested by comparing the desired and the simulated values of the multiple objectives. The result show that the knowledge acquisition and refinement method is effective for the multi-objective and multi-decision FMS scheduling problems.

• Proceedings of the Korean Society for Agricultural Machinery Conference
• /
• 1996.06c
• /
• pp.679-684
• /
• 1996

The work was aimed at realize the problem of seed processing . Solving this problem it was ascertained that the existing mathematical methods are reliable enough, but they are used practically very seldom. The work offers to use the expert system technology which allows to solve problems connected with practical knowledge of experts in the region of investigation effectively. The method of knowledge structuring and analizing as well as technique of knowledge acquisition which is necessary for realization of this technology are worked-out in the work. As the result applying the worked-out method the prototypes of the expert system (ES) are created : -ES " Sieves " ; research prototype for the sieve choice for the seed sorting machines -ES " Diagnostics " ; displaying prototype for the technological determination of action disrepair of seed sorting machines.

• Korean Journal of Clinical Pharmacy
• /
• v.32 no.4
• /
• pp.328-335
• /
• 2022

Background: Case-based learning (CBL) is becoming an important approach for improving interprofessional collaboration education. Previous studies have examined learners' satisfaction with interprofessional education (IPE) in medical institutions. However, there are few studies on the implementation of university-led CBL interventions and their direct effects on learning outcomes. The aim of this study was to evaluate the effectiveness of CBL interventions on changes in the participants' perception and knowledge acquisition ability. Methods: The CBL approach consisted of team-based case-based learning, self-directed learning, and post-feedback. It was conducted as a single course for pharmacy students in their 5th year in a university setting. Changes in the participants' perceptions and self-assessments of competence levels were evaluated using survey responses. The effect of the CBL intervention on knowledge acquisition ability was directly evaluated using the exam score. Results: The majority agreed or strongly agreed that team-based case-based learning, and self-directed learning helped them to improve their knowledge and skills to a higher level and to increase the self-assessment of competency level. The average score of knowledge acquisition ability (average score of 75.0, p=0.0098) was significantly higher in the CBL intervention group than the lecture-based learning intervention group (average score of 52.0). Conclusion: The participants positively perceived that CBL intervention helped them to effectively improve their knowledge and the self-assessment of competency level. It also enhanced knowledge acquisition ability. These data, based on the survey responses, suggest that it is necessary to implement CBL interventions in a university-led single professional education.

• Knowledge Management Research
• /
• v.10 no.1
• /
• pp.1-15
• /
• 2009

As pervasive computing technology, which aims to get linked to useful knowledge, information or services anytime, anywhere, using any devices and/or artifacts, is proliferating, desirable impacts on knowledge management systems are now available. The pervasive computing technology will potentially enable the knowledge management systems to realize individualization and socialization and ultimately increase the knowledge processing productivity. However, researchers who apply the pervasive computing methodologies to novel way of knowledge management have been very few. These result in unsatisfactory consideration of establishing pervasive knowledge management systems. Hence, the purpose of this paper is to cast the vision of pervasive knowledge management and search for a couple of possible research issues and possibilities. This paper suggests a framework of ubiDSS, an amended knowledge management system for the next generation deploying pervasive and autonomous knowledge acquisition capabilities of ubiquitous computing technologies. Also the CKAM, context-based knowledge acquisition module, is illustrated as a prototype of future knowledge management systems.