• Informatization Policy
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• v.30 no.3
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• pp.29-48
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• 2023

This study aims to investigate empirically the structural relationships among the components of data governance and their impacts on data integration and data-based administration. Through literature review, various definitions, typologies, and case studies of data governance were examined, with the definition of data governance from a public policy perspective developed and applied. The study then analyzed the data from a survey conducted by the Korea Institute of Public Administration on the use of public data policies and confirmed that organizational factors play a mediating role between institutional and technical factors, and that institutional and technical factors have statistically significant positive relationships with data fusion and data-driven administration. Based on these results, interest and investment in the improvement and development of the legal system in data governance from the institutional, technical, and organizational perspective, clarification of means and purposes of data technology, interest in data organizations and human resources, and practical operation can be achieved. Policy implications such as the development of an effective mechanism were presented.

• Journal of Technology Innovation
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• v.5 no.2
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• pp.1-21
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• 1997

The objective of this paper is to think about what structural reforms of the Korean government S&T development management system might be. Korean society is currently experiencing a drastic socio-economic transformation. The results of this transformation should be reflected on the determining process of the directions and breadths of structural reforms of government S&T development management system. Because the government system design will be based on the premises of socio-economic conditions under which administrative activities perform and also this socio-economic changes can influence on changes of the premises of government management system design. Moreover, S&T development management system is a subsystem of government system so that the directions of structural reform of those subsystems should be considered in the broad framework changes in the development management system of the government. For the last forty years, the Korean government S&T development management system has been based on the premises including transformation from an agrarian society to an industrial society, authoritarianism and centrally controlled institutions, and exteremely small portions of private investments for science and thechonology R & D of the total. Recently, however, the premises of Korean government S&T development management system have rapidly changed. the characteristics of these changes are including tranformation from an industrial society to a knowledge and information intensive society, globalization, localization, and relatively large portion of private investments for science and technology R & C of the total. The basis of government reforms in Korea was the realization of the performances and values through the enhancement of national competitive capacity, attainment of lean government, decentralization and autonomy. However, the Korean government has attached a symbolic value of strategic organizations representing strong policy intentions of government for the science and technology based development. Most problems associated with the Korean government S&T development management system have grown worse during 1990s. Many people perceive that considerable part of this problem was generated because the government could not properly adapt itself to new administrative environment and the paradigm shift in its role. First of all, the Korean government S&T development management system as a whole failed to develop an integrated vision under which processes in formulating science and thechology development goals and developing consistent government plans concerning science and technology development are guided. Second, most of the local governments have little organizational capacity and manpowers to handle localized activities to promote science and technology in their regions. Third, the measure to coordinate and set priorities to invest resources for the development of science and technology was not effective. Fourth, the Most has been losing its reputation as the symbol of ideological commitment of the top policy maker to promote science and technology. Various ideas to reform government S&T development management system have been suggested recently. Most frequently cited ideas are as follow : (ⅰ)strengthen the functions of MoST by supplementing the strong incentive and regulatory measures; (ⅱ)create a new Ministry of Education, Science & Technology and Research by merging the Ministry of Education and the MoST; (ⅲ)create a new Ministry of Science & Technology and Industry ; and(ⅳ)create a National Science and Technology Policy Council under the chairmanship of the President. Four alternatives suggested have been widely discussed among the interested parties and they each have merits as well as weaknesses. The first alternative could be seen as an alternative which cannot resolve current conflicts among various ministries concerning priority setting and resource allocation. However, this alternatives can be seen as a way of showing the top policymaker's strong intention to emphasize science and technology based development. Second alternative is giving a strategic to emphasize on the training and supplying qualified manpower to meet knowledge and information intensive future society. This alternative is considered to be consistent with the new administrative paradigm emphasizing lean government and decentralization. However, opponents are worrying about the linkages and cooperative research between university and industry could be weakening. The third alternative has been adopted mostly in nations which have strong basic science research but weak industrial innovation traditions. Main weakness of this alternative for Korea is that Korean science and technology development system has no strong basic science and technology research traditions. The fourth alternative is consistent with new administrative paradigms and government reform bases. However, opponents to this alternative are worried that the intensive development of science and technology because of Korea's low potential research capabilities in science and technology development. Considerning the present Korean socio-economic situation which demands highly qualified human resources and development strategies which emphasizes the accumulations of knowledge-based stocks, I would like to suggest the route of creating a new Ministry of Education, Science & Technology and Research by intergrating education administration functions and science & technology development function into one ministry.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.1-23
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• 2019

Big data refers to data that is difficult to store, manage, and analyze by existing software. As the lifestyle changes of consumers increase the size and types of needs that consumers desire, they are investing a lot of time and money to understand the needs of consumers. Companies in various industries utilize Big Data to improve their products and services to meet their needs, analyze unstructured data, and respond to real-time responses to products and services. The financial industry operates a decision support system that uses financial data to develop financial products and manage customer risks. The use of big data by financial institutions can effectively create added value of the value chain, and it is possible to develop a more advanced customer relationship management strategy. Financial institutions can utilize the purchase data and unstructured data generated by the credit card, and it becomes possible to confirm and satisfy the customer's desire. CRM has a granular process that can be measured in real time as it grows with information knowledge systems. With the development of information service and CRM, the platform has change and it has become possible to meet consumer needs in various environments. Recently, as the needs of consumers have diversified, more companies are providing systematic marketing services using data mining and advanced CRM (Customer Relationship Management) techniques. KB Kookmin Card, which started as a credit card business in 1980, introduced early stabilization of processes and computer systems, and actively participated in introducing new technologies and systems. In 2011, the bank and credit card companies separated, leading the 'Hye-dam Card' and 'One Card' markets, which were deviated from the existing concept. In 2017, the total use of domestic credit cards and check cards grew by 5.6% year-on-year to 886 trillion won. In 2018, we received a long-term rating of AA + as a result of our credit card evaluation. We confirmed that our credit rating was at the top of the list through effective marketing strategies and services. At present, Kookmin Card emphasizes strategies to meet the individual needs of customers and to maximize the lifetime value of consumers by utilizing payment data of customers. KB Kookmin Card combines internal and external big data and conducts marketing in real time or builds a system for monitoring. KB Kookmin Card has built a marketing system that detects realtime behavior using big data such as visiting the homepage and purchasing history by using the customer card information. It is designed to enable customers to capture action events in real time and execute marketing by utilizing the stores, locations, amounts, usage pattern, etc. of the card transactions. We have created more than 280 different scenarios based on the customer's life cycle and are conducting marketing plans to accommodate various customer groups in real time. We operate a smart offering system, which is a highly efficient marketing management system that detects customers' card usage, customer behavior, and location information in real time, and provides further refinement services by combining with various apps. This study aims to identify the traditional CRM to the current CRM strategy through the process of changing the CRM strategy. Finally, I will confirm the current CRM strategy through KB Kookmin card's big data utilization strategy and marketing activities and propose a marketing plan for KB Kookmin card's future CRM strategy. KB Kookmin Card should invest in securing ICT technology and human resources, which are becoming more sophisticated for the success and continuous growth of smart offering system. It is necessary to establish a strategy for securing profit from a long-term perspective and systematically proceed. Especially, in the current situation where privacy violation and personal information leakage issues are being addressed, efforts should be made to induce customers' recognition of marketing using customer information and to form corporate image emphasizing security.

• Journal of Korea Society of Industrial Information Systems
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• v.8 no.3
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• pp.51-60
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• 2003

In the radical char]go of the business environments that the existing facilities can not guarantee the business-frosts anymore, enterprises have been importing ERP system. In Korea, Sam-sung Electronics did it for the first tin in the latter half of 1994 and other enterprises succeeded. Currently, government and public enterprises as well as most of the large enterprises are employing ERP system to sharpen the competitiveness and to win the business transparency. On the other hand, it is harder for small and medium enterprises shaded by the large enterprises to be well-equipped with information system such as ERP, because they have already suffered from chronic financial difficulties and shortage of many resources. Most of all, they prefer the short-term project that does not need much tine for them to make decisions and to carry out fully. Grounded on the above factors, in this work, I suggest the suitable ERP model for the small and medium enterprises and the successful importing process of ERP, which is derived from the previous researches made by other masters' thesis. If necessary information and human resources are interchanged pertinently between local education institute and small and medium enterprise, the latter could not only deal with the confronted difficulties successfully inside and outside but attain the goal of being proficient in up-to-minute high technology. Besides, giving the students the opportunity of researching into the practice of the business they have not ever known, local universities could help their students accumulate knowledges and acquire ideas which could not be achieved in pure academic studies. When the above-mentioned procedure is over, the students might get the intellectual faculty to ponder on the future more concretely and enter a profession more carefully. In the result, we would raise up the percentage of the employment among the graduates. And active participation of university professors is the last important factor that assists the small and medium enterprises for introducing ERP system successfully. Their scholarly attainments play an important role in strengthening local economy and make the business competitiveness balanced between the capital and the local economy.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.159-185
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• 2016

Planning a multi-day trip is a complex, yet time-consuming task. It usually starts with selecting a list of points of interest (POIs) worth visiting and then arranging them into an itinerary, taking into consideration various constraints and preferences. When choosing POIs to visit, one might ask friends to suggest them, search for information on the Web, or seek advice from travel agents; however, those options have their limitations. First, the knowledge of friends is limited to the places they have visited. Second, the tourism information on the internet may be vast, but at the same time, might cause one to invest a lot of time reading and filtering the information. Lastly, travel agents might be biased towards providers of certain travel products when suggesting itineraries. In recent years, many researchers have tried to deal with the huge amount of tourism information available on the internet. They explored the wisdom of the crowd through overwhelming images shared by people on social media sites. Furthermore, trip planning problems are usually formulated as 'Tourist Trip Design Problems', and are solved using various search algorithms with heuristics. Various recommendation systems with various techniques have been set up to cope with the overwhelming tourism information available on the internet. Prediction models of recommendation systems are typically built using a large dataset. However, sometimes such a dataset is not always available. For other models, especially those that require input from people, human computation has emerged as a powerful and inexpensive approach. This study proposes CYTRIP (Crowdsource Your TRIP), a multi-day trip itinerary planning system that draws on the collective intelligence of contributors in recommending POIs. In order to enable the crowd to collaboratively recommend POIs to users, CYTRIP provides a shared workspace. In the shared workspace, the crowd can recommend as many POIs to as many requesters as they can, and they can also vote on the POIs recommended by other people when they find them interesting. In CYTRIP, anyone can make a contribution by recommending POIs to requesters based on requesters' specified preferences. CYTRIP takes input on the recommended POIs to build a multi-day trip itinerary taking into account the user's preferences, the various time constraints, and the locations. The input then becomes a multi-day trip planning problem that is formulated in Planning Domain Definition Language 3 (PDDL3). A sequence of actions formulated in a domain file is used to achieve the goals in the planning problem, which are the recommended POIs to be visited. The multi-day trip planning problem is a highly constrained problem. Sometimes, it is not feasible to visit all the recommended POIs with the limited resources available, such as the time the user can spend. In order to cope with an unachievable goal that can result in no solution for the other goals, CYTRIP selects a set of feasible POIs prior to the planning process. The planning problem is created for the selected POIs and fed into the planner. The solution returned by the planner is then parsed into a multi-day trip itinerary and displayed to the user on a map. The proposed system is implemented as a web-based application built using PHP on a CodeIgniter Web Framework. In order to evaluate the proposed system, an online experiment was conducted. From the online experiment, results show that with the help of the contributors, CYTRIP can plan and generate a multi-day trip itinerary that is tailored to the users' preferences and bound by their constraints, such as location or time constraints. The contributors also find that CYTRIP is a useful tool for collecting POIs from the crowd and planning a multi-day trip.

• Spatial Information Research
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• v.16 no.3
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• pp.279-290
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• 2008

Landslide, one of the serious natural disasters, has Incurred a large loss of human and material resources. Recently, many forecasting or alarm systems based on various kinds of measuring equipment have been developed to reduce the damage of landslide. However, only a few of these equipments are guaranteed to evaluate the safety of whole side of land slope with their accessibility to the slope. In this study, we performed some experiments to evaluate the applicability of a terrestrial LiDAR as a surveying tool to measure the displacement of a land slope surface far a slope collapsing protection system. In the experiments, we had applied a slope stability method to a land slope and then forced to this slope with a load increasing step by step. In each step, we measured the slope surface with both a total station and a terrestrial LiDAR simultaneously. As the result of Slope Fracturing analysis using all targets, the LiDAR system showed that three was 1cm RMSE on X-axis, irregularity errors on Y-axis and few errors on Z-axis compare with Total Station. As the result of Slope Fracturing analysis using continuous targets, the pattern of Slope Fracturing was different according to the location of continuous targets and we could detect a continuous change which couldn't be found using Total station. The accuracy of the LiDAR data was evaluated to be comparable to that of the total station data. We found that a LiDAR system was appropriate to measuring the behaviour of land slope. The LiDAR data can cover the whole surface of the land slope, whereas the total station data are available on a small number of targets. Moreover, we extracted more detail information about the behavior of land slope such as the volume and profile changes using the LiDAR data.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.179-192
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• 2014

Keeping in line with the recent changes in the information technology environment, the online learning environment that supports multiple users' participation such as MOOC (Massive Open Online Courses) has become important. One of the largest professional associations in Information Technology, IEEE Computer Society, announced that "Supporting New Learning Styles" is a crucial trend in 2014. Popular MOOC services, CourseRa and edX, have continued to build active learning environment with a large number of lectures accessible anywhere using smart devices, and have been used by an increasing number of users. In addition, collaborative web services (e.g., blogs and Wikipedia) also support the creation of various user-uploaded learning materials, resulting in a vast amount of new lectures and learning materials being created every day in the online space. However, it is difficult for an online educational system to keep a learner' motivation as learning occurs remotely, with limited capability to share knowledge among the learners. Thus, it is essential to understand which materials are needed for each learner and how to motivate learners to actively participate in online learning system. To overcome these issues, leveraging the constructivism theory and collective intelligence, we have developed a social bookmarking system called WeStudy, which supports learning material sharing among the users and provides personalized learning material recommendations. Constructivism theory argues that knowledge is being constructed while learners interact with the world. Collective intelligence can be separated into two types: (1) collaborative collective intelligence, which can be built on the basis of direct collaboration among the participants (e.g., Wikipedia), and (2) integrative collective intelligence, which produces new forms of knowledge by combining independent and distributed information through highly advanced technologies and algorithms (e.g., Google PageRank, Recommender systems). Recommender system, one of the examples of integrative collective intelligence, is to utilize online activities of the users and recommend what users may be interested in. Our system included both collaborative collective intelligence functions and integrative collective intelligence functions. We analyzed well-known Web services based on collective intelligence such as Wikipedia, Slideshare, and Videolectures to identify main design factors that support collective intelligence. Based on this analysis, in addition to sharing online resources through social bookmarking, we selected three essential functions for our system: 1) multimodal visualization of learning materials through two forms (e.g., list and graph), 2) personalized recommendation of learning materials, and 3) explicit designation of learners of their interest. After developing web-based WeStudy system, we conducted usability testing through the heuristic evaluation method that included seven heuristic indices: features and functionality, cognitive page, navigation, search and filtering, control and feedback, forms, context and text. We recruited 10 experts who majored in Human Computer Interaction and worked in the same field, and requested both quantitative and qualitative evaluation of the system. The evaluation results show that, relative to the other functions evaluated, the list/graph page produced higher scores on all indices except for contexts & text. In case of contexts & text, learning material page produced the best score, compared with the other functions. In general, the explicit designation of learners of their interests, one of the distinctive functions, received lower scores on all usability indices because of its unfamiliar functionality to the users. In summary, the evaluation results show that our system has achieved high usability with good performance with some minor issues, which need to be fully addressed before the public release of the system to large-scale users. The study findings provide practical guidelines for the design and development of various systems that utilize collective intelligence.

• Archives of design research
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• v.15 no.1
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• pp.59-67
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• 2002

In accordance with the fast changing circumstance, universities are now reaching, beyond the education place of simple delivery of knowledge and exchange of information, to a place of developing a specialty program related with the region and industry to achieve a competitive edge in education. Through these academic-industrial collaboration program, special knowledge and human resources in the university are utilized in the society and it may contribute to the development of industry and breed of career people based upon the real job site can be achieved. In addition, through the practical operation of such developed program, university may contribute to the enhancement of the competitiveness of the corporation to the activation and acceleration of the regional economy and finally to the enhancement of competitiveness of national industry in international level. This study tries to develop 3 technical instruction and support program related with the legion and industry which may conform to the ideals of university and its goal of education and can provide a platform for the education that is closely related with the regional industry and real job site iud may cope actively with the upcoming knowledge society and fast changing regional circumstances. This study will make research and analyze needs of design support from the industry in order to develop a academic-industrial cooperative design support program for the furniture industry which conforms to the regional characteristic and feature and develop and present contents of program in three area of development of furniture design technology, build-up of furniture design information system and establishment of order based education system. The proposed program is supposed to be operated practically and effectively and contribute to the development of new product, to enhancement of company image and finally to the maximization of corporate profit. Also this study is epected to be used as an important material for establishment of order-based education system which confirms to the job site needs that may be analysed from feedback of product results and for practical learning.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.11
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• pp.87-104
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• 2015

Currently the IoT (Internet of Things) environments and related technologies are being developed rapidly through the networks for connecting many intelligent objects. The IoT is providing artificial intelligent services combined with context recognition based knowledge and communication methods between human and objects and objects to objects. With the help of IoT technology, many research works are being developed using the C-ITS (Cooperative Intelligent Transport System) which uses road infrastructure and traveling vehicles as traffic control infrastructures and resources for improving and increasing driver's convenience and safety through two way communication such as bus-only lane and license plate recognition and road accidents, works ahead reports, which are eventually for advancing traffic effectiveness. In this paper, a system for deciding whether the traveling vehicle is possible or not to drive on bus-only lane in highway is researched using the lane and number plate recognition on the road in C-ITS traffic infrastructure environments. The number plates of vehicles on the straight ahead and sides are identified after the location of bus-only lane is discovered through the lane recognition method. Research results and experimental outcomes are presented which are supposed to be used by traffic management infrastructure and controlling system in future.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.43-61
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• 2019

Development of technologies in artificial intelligence has been rapidly increasing with the Fourth Industrial Revolution, and researches related to AI have been actively conducted in a variety of fields such as autonomous vehicles, natural language processing, and robotics. These researches have been focused on solving cognitive problems such as learning and problem solving related to human intelligence from the 1950s. The field of artificial intelligence has achieved more technological advance than ever, due to recent interest in technology and research on various algorithms. The knowledge-based system is a sub-domain of artificial intelligence, and it aims to enable artificial intelligence agents to make decisions by using machine-readable and processible knowledge constructed from complex and informal human knowledge and rules in various fields. A knowledge base is used to optimize information collection, organization, and retrieval, and recently it is used with statistical artificial intelligence such as machine learning. Recently, the purpose of the knowledge base is to express, publish, and share knowledge on the web by describing and connecting web resources such as pages and data. These knowledge bases are used for intelligent processing in various fields of artificial intelligence such as question answering system of the smart speaker. However, building a useful knowledge base is a time-consuming task and still requires a lot of effort of the experts. In recent years, many kinds of research and technologies of knowledge based artificial intelligence use DBpedia that is one of the biggest knowledge base aiming to extract structured content from the various information of Wikipedia. DBpedia contains various information extracted from Wikipedia such as a title, categories, and links, but the most useful knowledge is from infobox of Wikipedia that presents a summary of some unifying aspect created by users. These knowledge are created by the mapping rule between infobox structures and DBpedia ontology schema defined in DBpedia Extraction Framework. In this way, DBpedia can expect high reliability in terms of accuracy of knowledge by using the method of generating knowledge from semi-structured infobox data created by users. However, since only about 50% of all wiki pages contain infobox in Korean Wikipedia, DBpedia has limitations in term of knowledge scalability. This paper proposes a method to extract knowledge from text documents according to the ontology schema using machine learning. In order to demonstrate the appropriateness of this method, we explain a knowledge extraction model according to the DBpedia ontology schema by learning Wikipedia infoboxes. Our knowledge extraction model consists of three steps, document classification as ontology classes, proper sentence classification to extract triples, and value selection and transformation into RDF triple structure. The structure of Wikipedia infobox are defined as infobox templates that provide standardized information across related articles, and DBpedia ontology schema can be mapped these infobox templates. Based on these mapping relations, we classify the input document according to infobox categories which means ontology classes. After determining the classification of the input document, we classify the appropriate sentence according to attributes belonging to the classification. Finally, we extract knowledge from sentences that are classified as appropriate, and we convert knowledge into a form of triples. In order to train models, we generated training data set from Wikipedia dump using a method to add BIO tags to sentences, so we trained about 200 classes and about 2,500 relations for extracting knowledge. Furthermore, we evaluated comparative experiments of CRF and Bi-LSTM-CRF for the knowledge extraction process. Through this proposed process, it is possible to utilize structured knowledge by extracting knowledge according to the ontology schema from text documents. In addition, this methodology can significantly reduce the effort of the experts to construct instances according to the ontology schema.