• The Journal of the Korea Contents Association
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• v.10 no.11
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• pp.1-9
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• 2010

In comparison with the acquirement of knowledge by expression of symbol or numerical formula, the experience based knowledge acquirement give stable and clear understanding of information to a learner. Various educational systems based on computer such as virtual reality, intelligent learning system, visualization of concept, simulation-based system, and microworld have so far been developed. In this paper, a method of two dimensional visualization of a physical law by simulation has been suggested to educate a learner. Especially, learning the law of gravity by simulation based educational method gives a learner indirect experience that enhance the efficiency of knowledge acquirement clearly. The visualization methods of a real-time physical law and a virtual anomalies' physical law by simulation are proposed in this paper to deliver information or knowledge clearly. Then we show that a learner can acquire some knowledge effectively by the proposed method.

• Knowledge Management Research
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• v.14 no.5
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• pp.121-136
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• 2013

Augmented reality, which has recently drawn great attention, has along history in technical terms. However, the latest emergence of mobile augmented reality using smartphones is allowing people to access augmented reality more easily and faster than ever. However, a review of existing studies shows that most of them have focused on the technical realization of augmented reality, whereas few studies have dealt with how users perceive augmented reality. For users, augmented reality is a means of knowledge transfer, which enables the experience of more abundant reality by providing additional informatio nsources to objects or landscapes. There fore, the element of experience must be considered for the perception of users. In addition, the current augmented reality technology certainly provides users with more fun than any other existing technologies. In this regard, this study intended to divided experiences not only into sensory experiences, but also into entertainment, educational, escapist, and esthetic experiences based on the experience economy theory suggested by Pine and Gilmore(1998). Moreover, this study intended to examine whether mobile augmented reality applications, which are highly popular as a means of the experience economy, influence the usefulness, convenience, and enjoyment perceived by users, and to identify which of these cognitive elements influence usage intentions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.2022-2042
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• 2020

This research aims to contribute to the discipline of knowledge management (KM) in Higher Education (HE), and is conducted using the case of the study programme (SP) for Integrated Academic Studies (IAS) of Technics and Informatics (TI). A deduction-induction methodology is applied, using a Plan-Do-Check-Act (PDCA) approach to design a suitable KM concept for making improvements to the SP IAS TI on the standardisation platform. Based on the application of the International Classification of Standards (ICS), the research analyses the correlations and competences acquired during the courses within the accredited TI study programme of two-course studies. On the basis of the results of a comparative analysis of the developmental learning process and educational goals, it is shown that knowledge management in correlation with standardisation leads to the improvement of study programmes in the upcoming accreditation cycle on the standardisation platform. Frequent innovations within standardised thematic fields (daily, weekly, monthly, etc.) indicate the need for appropriate changes to the SP. The contribution to KM is through an original analysis of annual samples of more than 90,000 standardised sources in correlation with the TI study programme. Expert System (ES) modelling and the original results enable an analogous contribution to the future KM of other SPs.

• 한국IT서비스학회:학술대회논문집
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• 2008.11a
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• pp.127-130
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• 2008

Recently, a wide variety of research on the knowledge-based industries, which are considered a key area of social science research, has been conducted. In this light, this study examines a case of knowledge diffusion taken from the IT service field. The IT service industry has been considered difficult to diffuse due to its unique technological regimes and sophisticated market demand. In particular, the established public service systems have limited markets and encompass national characteristics, thereby making their international diffusion difficult. However, despite these limitations, the automated customs system ASYCUDA has been distributed successfully and is now operating in about 100 countries, making the case very unusual. Using various industrial innovation models, and an analysis of lead markets, with regard to ASYCUDA, this research examines patterns of technological learning activities by actors, characteristics of the lead markets, and paths of technology transfer. The findings indicate that when active technology providers attempt to streamline and standardize the technology to make it suitable for the characteristics of the initial technology application areas(lead markets), this helps to diffuse the technology to passive recipients and the surrounding nations. The findings also confirm that south-south cooperation in the acquired technologies was of considerable help in sharing knowledge among the passive technology recipients, and that the active technology providers' programmed, well-organized technology assistance was a key driving force behind technology transfer and diffusion between the surrounding nations.

• Journal of Information Processing Systems
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• v.5 no.3
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• pp.159-166
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• 2009

As shown in Wikipedia, tagging or cross-linking through major keywords in a document collection improves not only the readability of documents but also responsive and adaptive navigation among related documents. In recent years, the Semantic Web has increased the importance of social tagging as a key feature of the Web 2.0 and, as its crucial phenotype, Tag Cloud has emerged to the public. In this paper we provide an efficient method of automated in-text keyword tagging based on large-scale controlled term collection or keyword dictionary, where the computational complexity of O(mN) - if a pattern matching algorithm is used - can be reduced to O(mlogN) - if an Information Retrieval technique is adopted - while m is the length of target document and N is the total number of candidate terms to be tagged. The result shows that automatic in-text tagging with keywords filtered by Information Retrieval speeds up to about 6 $\sim$ 40 times compared with the fastest pattern matching algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.347-354
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• 2022

To reduce forgetfulness in continuous learning, in this paper, we propose an improved LwF model based on the knowledge transfer method, and we show its effectiveness by experiment. In LwF, if the domain of the learned data is different or the complexity of the data is different, the previously learned results are inaccurate due to forgetting. In particular, when learning continues from complex data to simple data, the phenomenon tends to get worse. In this paper, to ensure that the previous learning results are sufficiently transferred to the LwF model, we apply the knowledge transfer method to LwF, and propose an algorithm for efficient use. As a result, the forgetting phenomenon was reduced by an average of 8% compared to the existing LwF results, and it was effective even when the learning task became long. In particular, when complex data was first learned, the efficiency was improved more than 30% compared to LwF.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.571-573
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• 2021

Recently, according to the rapid development of the Internet, information is increasing exponentially. A lot of this information Various studies are being conducted in order to communicate smoothly. In recent years, related researches applying artificial intelligence and big data technologies have been actively conducted. However, it has not produced remarkable results. One of the causes can be found in the severe limitation of the lack of language and knowledge standards. Currently, there is an active research on conferences using a multimedia approach, and gradually, interest in knowledge-based conference systems has begun. In the case of a meeting with a multimedia approach, the advantages and disadvantages of the existing offline meetings are expressed online as they are, and the management of information on the actual contents and process of important meetings is neglected. Therefore, in this paper, we study a plan to convert conference content information into an ontology, and propose a method to systematically analyze the ontology-formed information.

• Information Systems Review
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• v.18 no.3
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• pp.111-135
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• 2016

The major characteristic of open source software (OSS) is innovativeness. Innovativeness stems from the process of sharing and solving technical problems. This study analyzes the impact of voluntary participation and collaboration of OSS developers on sustained participation in the community based on organizational citizenship behavior and social capital theories. Based on Bolino et al. (2002) and Wasko and Faraj (2005), a research model and hypotheses are developed. A total of 152 OSS developers participated in the survey. The hypotheses are tested by LISREL modeling. The results of analysis show that royalty, social participation, and advocacy participation enhance or positively influence social capital. In addition, reciprocity and shared vision reinforce intention of sustained knowledge contribution. However, the result shows a statistically insignificant relationship between social participation and shared vision and between cohesiveness and intention of sustained knowledge contribution.

• The Journal of the Korea Contents Association
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• v.10 no.10
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• pp.479-493
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• 2010

Along with the transformation of the knowledge-based environment, e-learning has become a main teaching and learning method, prompting various research efforts to be conducted in this field. One major research area in e-learning involves adaptive learning systems that provide personalized learning content according to each learner's characteristics by taking into consideration a variety of learning circumstances. Active research on ontology-based adaptive learning systems has recently been conducted to provide more efficient and adaptive learning content. In this paper, we design and propose an adaptive learning system based on the concept lattice of Formal Concept Analysis (FCA) with the same objectives as those of ontology approaches. However, we are in pursuit of a system that is suitable for learning of specific domains and one that allows users to more freely and easily build their own adaptive learning systems. The proposed system automatically classifies the learning objects and concepts of an evolved domain in the structure of a concept lattice based on the relationships between the objects and concepts. In addition, the system adaptively constructs and presents the learning structure of the concept lattice according to each student's level of knowledge, learning style, learning preference and the learning state of each concept.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.2122-2140
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• 2020

Proper and precise embedding of commercial ads within Webpages requires Ad-hoc analysis and understanding of their content. By the successful implementation of this step, both publishers and advertisers gain mutual benefits through increasing their revenues on the one hand, and improving user experience on the other. In this research work, we propose a novel multi-level context-based ads serving approach through which ads will be served at generic publisher websites based on their contextual relevance. In the proposed approach, knowledge encoded in domain-specific and generic semantic repositories is exploited in order to analyze and segment Webpages into sets of contextually-relevant segments. Semantically-enhanced indexes are also constructed to index ads based on their textual descriptions provided by advertisers. A modified cosine similarity matching algorithm is employed to embed each ad from the Ads repository into one or more contextually-relevant segments. In order to validate our proposal, we have implemented a prototype of an ad serving system with two datasets that consist of (11429 ads and 93 documents) and (11000 documents and 15 ads), respectively. To demonstrate the effectiveness of the proposed techniques, we experimentally tested the proposed method and compared the produced results against five baseline metrics that can be used in the context of ad serving systems. In addition, we compared the results produced by our system with other state-of-the-art models. Findings demonstrate that the accuracy of conventional ad matching techniques has improved by exploiting the proposed semantically-enhanced context-based ad serving model.