• The Journal of Information Systems
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• v.1
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• pp.149-178
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• 1992

The field of Artificial Intelligence (AI) is growing, and many firms are investing in expert system, one of AI's subfields. An expert system is defined as a computer program designed to replicate some aspect of the decision making of one or more experts and to be used by nonexperts. The kernel of an expert system is the knowledge base, which consists of the facts and rules that represent the expert's knowledge. Firms need expert systems for training employees to provide competitive advantage. This paper describes the model of an instructional expert training system which interfaces to external programs, such as an ASCII file, a work-sheet program, and a database program. A model for such an expert training system, and its prototype have been developed to demonstrate its functionality. A modular knowledge base has been developed and implemented in support of this study. The modularized knowledge base offers the user an easy and quick maintenance of facts and rules, which are frequently required to change in future.

• English Language & Literature Teaching
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• v.9 no.2
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• pp.213-241
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• 2003

As an attempt to characterize the English test section of CSAT (College Scholastic Ability Test) and to get some suggestions, this study raised the research questions, as 'What are the main factors that affect students' English test scores in CSAT, and how big influences do they have?' It has been hypothesized that among main factors are the L1 competence, represented by the Korean test scores in CSAT, background knowledge or intelligence, represented by the "total" scores in CSAT, and the two types of L2 knowledge (vocabulary and grammar on one hand and prosody m the other hand), measured by the test devised specially for this study. The individual effect of the L2 vocabulary and grammar (one kind of L2 knowledge) was 70%, that of background knowledge or intelligence 61%, that of the L1 competence 50%, and that of the L2 prosody knowledge (the other kind of L2 knowledge) 32%. According to the stepwise regression, the whole effect of these four factors was 74%. The findings suggest that first, although CSAT is based on the top-down model of comprehension, the bottom-up model of learning should be more emphasized in our English class. Also, since background knowledge or intelligence is the second most influential factor, the top-down model of learning that helps students learn to understand by activating their various schemata must also be very effective.

• Journal of Information Technology Services
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• v.17 no.1
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• pp.1-16
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• 2018

In this research, we tried to suggest the guidelines to stakeholder of ICT startup for picking up the excellent startups and nurturing them. We designed the research model focused on the good startup team's knowledge based interaction mechanism. A research model and hypotheses were developed from literature review and empirically validated. The research model consisted relationship among the knowledge sharing (knowledge donation and knowledge collection), absorptive capacity (member's ability and member's motivation), team creativity, and innovation capability. Data were collected from ICT Service Startups, and a partial least squares (PLS) analysis was made on 175 data points. The analysis results showed that absorptive capacity has significant effect on team creativity and innovation capability directly. And also it has indirect effect on the dependent variable through team creativity. On the contrary, knowledge sharing does not have statistically significant effect on team creativity and innovation capability; only have an effect on absorptive capacity. Based on the results, we proposed several team management skills for ICT startup leaders and members, and the guidelines to stakeholder such as government and private investors. Also there are some ideas for startup nurturing polices for government officers. Theoretical contributions are discussed at the end with limitations and further studies.

• Journal of Korean Elementary Science Education
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• v.25 no.spc5
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• pp.465-475
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• 2007

The purpose of this study was to develop a spider inquiry program for elementary school students based on the scientific-knowledge generating model. For the purposes of this study, we selected three species of snider (e.g. Pardosa astrigera, Argiope bruennichii, Nephila clavata) which were easily found in a school garden by elementary school students. The spider inquiry program was based on a model of the process of scientific-knowledge generation, and consisted of two sections: for students and teachers. The students' program was designed to generate scientific-knowledge, whilst the teachers' program was designed to guide the inquiry smoothly even in the case of teachers who lack experience in inquiry activities or possess limited subject knowledge on spiders. As a result, this program was found to have an influence on generating the scientific-knowledge of elementary students and the results further suggest that it may be helpful to teachers conducting an inquiry activity. Additionally, this program could be used as a selective activity lesson such as a science inquiry lesson, or as a biology inquiry class, as a weekend life experience study or as an activity on a science camp.

• Journal of Korean Library and Information Science Society
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• v.33 no.4
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• pp.209-240
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• 2002

This study worts on how to change the public library paradigm in the side view of library faculties and environments, digital library, culture and structure. Also, here manages the need of knowledge management and components with the status problem of public library for a basis. This study aims to propose the total knowledge management model based on the knowledge management frameworks ; management strategy, the human resources, processing, and network.

• Journal of Information Processing Systems
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• v.17 no.5
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• pp.867-878
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• 2021

In context awareness and user intention tasks, dataset construction is expensive because specific domain data are required. Although pretraining with a large corpus can effectively resolve the issue of lack of data, it ignores domain knowledge. Herein, we concentrate on data domain knowledge while addressing data scarcity and accordingly propose a multi-channel long short-term memory (LSTM). Because multi-channel LSTM integrates pretrained vectors such as task and general knowledge, it effectively prevents catastrophic forgetting between vectors of task and general knowledge to represent the context as a set of features. To evaluate the proposed model with reference to the baseline model, which is a single-channel LSTM, we performed two tasks: voice phishing with context awareness and movie review sentiment classification. The results verified that multi-channel LSTM outperforms single-channel LSTM in both tasks. We further experimented on different multi-channel LSTMs depending on the domain and data size of general knowledge in the model and confirmed that the effect of multi-channel LSTM integrating the two types of knowledge from downstream task data and raw data to overcome the lack of data.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.410-420
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• 2001

A primitive conceptualization is defined as the set of all intended situations. A non-primitive conceptualization is defined as the set of all the pairs every of which consists of an intended knowledge system and the set of all the situations admitted by the knowledge system. The reality of a domain is considered as the set of all the situation which have ever taken place in the past, are taking place now and will take place in the future. A conceptualization is defined as precise if the set of intended situations is equal to the domain reality. The representation of various elements of a domain ontology in a model of the ontology is considered. These elements are terms for situation description and situations themselves, terms for knowledge description and knowledge systems themselves, mathematical terms and constructions, auxiliary terms and ontological agreements. It has been shown that any ontology representing a conceptualization has to be non-primitive if either (1) a conceptualization contains intended situations of different structures, or (2) a conceptualization contains concepts designated by terms for knowledge description, or (3) a conceptualization contains concept classes and determines properties of the concepts belonging to these classes, but the concepts themselves are introduced by domain knowledge, or (4) some restrictions on meanings of terms for situation description in a conceptualization depend on the meaning of terms for knowledge description.

• Journal of Information Processing Systems
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• v.2 no.2
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• pp.124-129
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• 2006

With the explosive increase in the generation and utilization of spatiotemporal data sets, many research efforts have been focused on the efficient handling of the large volume of spatiotemporal sets. With the remarkable growth of ubiquitous computing technology, mining from the huge volume of spatiotemporal data sets is regarded as a core technology which can provide real world applications with intelligence. In this paper, we propose a 3-tier knowledge discovery framework for spatiotemporal data mining. This framework provides a foundation model not only to define the problem of spatiotemporal knowledge discovery but also to represent new knowledge and its relationships. Using the proposed knowledge discovery framework, we can easily formalize spatiotemporal data mining problems. The representation model is very useful in modeling the basic elements and the relationships between the objects in spatiotemporal data sets, information and knowledge.

• Asia pacific journal of information systems
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• v.24 no.3
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• pp.281-297
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• 2014

This study aims at empirically analyzing the relation between employees' personality and their knowledge sharing intentions, on which enough light has not yet been shed in spite of its importance. By integrating the big five model of personality with social capital theory and social cognitive theory, this study develops six hypotheses concerning the relation and empirically tests them by using 724 samples collected from employees in practice. The empirical analysis results from this study reveal that employees' extroversion and agreeableness are positively associated with their social relations and that their openness to experience and conscientiousness are positively associated with their knowledge self-efficacy, which are positively related to their knowledge sharing intentions. Based on the new findings, theoretical and practical implications are provided for knowledge management researchers and managers in practice.

• Proceedings of the Korean System Dynamics Society
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• 2000.07a
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• pp.29-45
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• 2000

The purpose of this paper is understanding the dynamics of knowledge based industries in Korea and suggesting policy recommendations for supporting those industries. Following KIETs (1999) definition of knowledge intensity, this paper classified industries in Kyung Ki Province according to several knowledge indicators including R＆D activity and human capital content. Having classified industries, this paper investigates growth dynamics of knowledge based industries in Kyung-Ki Province. Based on surveys on some 280 knowledge based industries in Kyung-Ki province, growth path of those industries were identified using path analysis. Using the growth path and coefficient identified by the analysis, system dynamics model was build to simulate dynamics of knowledge based industries in Kyung-Ki province. With the model, further analysis was made to investigate some policy measures that can promote knowledge based industries.