• Korean System Dynamics Review
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• v.17 no.3
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• pp.31-50
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• 2016

This study examines the basic conditions of joint authorship research activities in the Korean System Dynamics Review and points out the structural co-author network characteristics among co-authored papers based on the social network analysis(SNA) techniques. In specific, this study identifies the cooperative relationship of research papers in the Korean System Dynamics Review, knowledge formation, and knowledge propagation paths. The study results imply that Korean System Dynamics Review has exhibited the typical 'Steven's power law,' which is repeatedly observed among complex systems, and that knowledge structure centered upon and propagated around couples of researchers. Additionally, the study results present that there have been active personal exchanges among major researchers. In contrast, personal contacts among research groups and within groups seem relatively weak.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.1996-2011
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• 2021

To understand a trend is to explore the intricate process of how something or a particular situation is constantly changing or developing in a certain direction. This exploration is about observing and describing an unknown field of knowledge, not testing theories or models with a preconceived hypothesis. The purpose is to gain knowledge we did not expect and to recognize the associations among the elements that were suspected or not. This generally requires examining a massive amount of data to find information that could be transformed into meaningful knowledge. That is, looking through the lens of big-data analytics with an inductive reasoning approach will help expand our understanding of the complex nature of a trend. The current study explored the trend of well-being in South Korea using big-data analytic techniques to discover hidden search patterns, associative rules, and keyword signals. Thereafter, a theory was developed based on inductive reasoning - namely the hook, upward push, and downward pull to elucidate a holistic picture of how big-data implications alongside social phenomena may have influenced the well-being trend.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.4
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• pp.209-215
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• 2022

This paper proposes a novel approach for training an unsupervised depth estimation algorithm. The objective of unsupervised depth estimation is to estimate pixel-wise distances from camera without external supervision. While most previous works focus on model architectures, loss functions, and masking methods for considering dynamic objects, this paper focuses on the training framework to effectively use depth cue. The main loss function of unsupervised depth estimation algorithms is known as the photometric error. In this paper, we claim that direct depth cue is more effective than the photometric error. To obtain the direct depth cue, we adopt the technique of knowledge distillation which is a teacher-student learning framework. We train a teacher network based on a previous unsupervised method, and its depth predictions are utilized as pseudo labels. The pseudo labels are employed to train a student network. In experiments, our proposed algorithm shows a comparable performance with the state-of-the-art algorithm, and we demonstrate that our teacher-student framework is effective in the problem of unsupervised depth estimation.

• Journal of Information Management
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• v.31 no.2
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• pp.1-10
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• 2000

Many experts predict that 21st century will be knowledge-based society. That is, knowledge beside labor, capital will be recognised as important assets and powerful competitiveness. The main aim of government-supported research institute is to evolve R&D activities and to diffuse them. And all process including R&D activities can be called to knowledge life cycle. This paper reviews understanding of KM and information professional's role in research information center. Sometimes, CEOs misunderstand that only building of knowledge management system is sucess of knowledge management initiatives but the most important factors of its success are human and culture of knowledge sharing, not H/W systems. Information professionals must be consultant, analyst, content manager, planner and marketer, knowledge manager to practice knowledge management initiatives successfully.

• Journal of Intelligence and Information Systems
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• v.14 no.1
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• pp.67-84
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• 2008

This paper proposes a design and realization for the semantic search system. The proposed model includes three Architecture Layers of a Semantic Search System ; (they are conceptually named as) the Knowledge Acquisition, the Knowledge Representation and the Knowledge Utilization. Each of these three Layers are designed to interactively work together, so as to maximize the users' information needs. The Knowledge Acquisition Layer includes index and storage of Semantic Metadata from various source of web contents(eg : text, image, multimedia and so on). The Knowledge Representation Layer includes the ontology schema and instance, through the process of semantic search by ontology based query expansion. Finally, the Knowledge Utilization Layer includes the users to search query intuitively, and get its results without the users'knowledge of semantic web language or ontology. So far as the design and the realization of the semantic search site is concerned, the proposedsemantic search system will offer useful implications to the researchers and practitioners so as to improve the research level to the commercial use.

• Journal of the Korean Society for Library and Information Science
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• v.53 no.1
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• pp.33-55
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• 2019

Knowledge information resources produced by policy research institutes were categorized into knowledge information resources derived from research processes, knowledge information resources derived from research results, and knowledge information resources processed from research results, respectively. The names of these knowledge information resources and the metadata items were investigated on 13 policy research institute websites. In addition, the study examined the provision status of 8 Knowledge information resources specialized by type on the websites and confirmed that they work as knowledge resource management systems for each corresponding area. The results of the study suggest constructing a collective search system for research results based on the same research topics, developing a knowledge map of policy information, compressing reports for policy makers, building subject expert databases, producing video reports, developing metadata standards, and creating statistical databases and indicators by subject areas.

• Information Systems Review
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• v.16 no.3
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• pp.25-47
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• 2014

IT project is a knowledge-based project with high uncertainty in role assignment and task allocationamong team members. This study empirically investigate steam members' interactive behavior in IT projects based on the framework of social interdependence theory. The goal and task interdependencebetween team members were posited as antecedents of project performance with communication effectiveness and knowledge sharing as mediating variables. To test the research model, a dataset was collected form IT and business professional pairs of 123 IT project teams. The results indicated that the theory of social interdependence is applicable to explaining the promotive interaction in IT project teams. In detail, task interdependence appears to have influence on both promotive interactions (communication effectiveness and knowledge sharing), and goal interdependence influences only on communication effectiveness. Knowledge sharing is found to be a significant mediator between social interdependence and project performance. However, communication effectiveness only indirectly influences project performance via knowledge sharing. Academic and practical implications are discussed.

• Journal of the Korean Society for information Management
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• v.37 no.2
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• pp.353-379
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• 2020

This study developed a user experience factors for the evaluation of knowledge and information resource system from the user experience perspectives, which is emerging as a new analysis standard in the field of information media and information service research. Based on the analysis criteria selected through literature analysis, 'system perception factor' and 'user experience factor' were derived as factors influencing the use of information systems through an experimental study based on the user experience sampling method. As a result, the user experience factors of final knowledge and information resource system includes nine user experience factors, 55 detailed user experience factors, and 138 system perception factors. This study is significant in that the abstract concept 'user experience' was derived and presented as a practical, concrete, measurable factor through experiments. The derived user experience factors should serve as a basis for measuring user experience perceived by users of the knowledge and information resource system.

• Journal of the Korea Convergence Society
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• v.10 no.7
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• pp.7-14
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• 2019

Users who use smartphone can using knowledge-based authentication, possession-based authentication, biometric-based authentication, and token-based authentication in order to access rights to systems requiring authentication. However, desktop computer users use method only ID and password, which are knowledge-based authentication factors, due to limitations of authentication devices, despite various authentication methods. In this paper, we designed and implemented a raspberry pi based authentication system that provides multiple authentication method of a user's desired type. The implementation system uses knowledge-based authentication, possessive-based authentication, biometric-based authentication, and token-based authentication. The proposed system can provide a security function that can be used by SMEs, which is difficult to hire a security officer due to the economic burden. The implemented system can be used not only for personal use but also for enterprise, and it can be applied to various fields such as finance and game.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.597-603
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• 2023

The paradigm of military operations has evolved from platform-centric warfare to network-centric warfare and further to information-centric warfare, driven by advancements in information technology. In recent years, with the development of cutting-edge technologies such as big data, artificial intelligence, and the Internet of Things (IoT), military operations are transitioning towards knowledge-centric warfare (KCW), based on artificial intelligence. Consequently, the military places significant emphasis on integrating advanced information and communication technologies (ICT) to establish reliable C4I (Command, Control, Communication, Computer, Intelligence) systems. This research emphasizes the need to apply data mining techniques to analyze and evaluate various aspects of C4I systems, including enhancing combat capabilities, optimizing utilization in network-based environments, efficiently distributing information flow, facilitating smooth communication, and effectively implementing knowledge sharing. Data mining serves as a fundamental technology in modern big data analysis, and this study utilizes it to analyze real-world cases and propose practical strategies to maximize the efficiency of military command and control systems. The research outcomes are expected to provide valuable insights into the performance of C4I systems and reinforce knowledge-centric warfare in contemporary military operations.