• Convergence Security Journal
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• v.13 no.3
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• pp.63-69
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• 2013

This research analyze the current status pertaining to the sport industry's information system and information network in Korea to propose integrated information network of sport industry construction measures with the goal of optimizing vertical and horizontal network formation, and knowledge information sharing and dissemination. To construct integrated information network of sport industry, literature examination and meeting of experts to search for measures are utilized. This paper analyze the realities of the sport industry's information system and information network in Korea to propose the following when it comes to the measures to realize sport industry's information integration. First, DB for sport industry relate information that factored in the Ontology is being developed. In other words, it is necessary to design a DB that factors in the Semantic Web. Second, once the DB relate to the sport industry that factored in the Ontology is developed, it is necessary to build RSS/Atom based active network that enables exchange of organic information among them.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.171-196
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• 2018

With the development of the web, two-way communication and evaluation became possible and marketing paradigms shifted. In order to meet the needs of consumers, web design trends are continuously responding to consumer feedback. As the web becomes more and more important, both academics and businesses are studying consumer emotions and satisfaction on the web. However, some consumer characteristics are not well considered. Demographic characteristics such as age and sex have been studied extensively, but few studies consider psychological characteristics such as regulatory focus (i.e., emotional regulation). In this study, we analyze the effect of web style on consumer emotion. Many studies analyze the relationship between the web and regulatory focus, but most concentrate on the purpose of web use, particularly motivation and information search, rather than on web style and design. The web communicates with users through visual elements. Because the human brain is influenced by all five senses, both design factors and emotional responses are important in the web environment. Therefore, in this study, we examine the relationship between consumer emotion and satisfaction and web style and design. Previous studies have considered the effects of web layout, structure, and color on emotions. In this study, however, we excluded these web components, in contrast to earlier studies, and analyzed the relationship between consumer satisfaction and emotional indexes of web-style only. To perform this analysis, we collected consumer surveys presenting 40 web style themes to 204 consumers. Each consumer evaluated four themes. The emotional adjectives evaluated by consumers were composed of 18 contrast pairs, and the upper emotional indexes were extracted through factor analysis. The emotional indexes were 'softness,' 'modernity,' 'clearness,' and 'jam.' Hypotheses were established based on the assumption that emotional indexes have different effects on consumer satisfaction. After the analysis, hypotheses 1, 2, and 3 were accepted and hypothesis 4 was rejected. While hypothesis 4 was rejected, its effect on consumer satisfaction was negative, not positive. This means that emotional indexes such as 'softness,' 'modernity,' and 'clearness' have a positive effect on consumer satisfaction. In other words, consumers prefer emotions that are soft, emotional, natural, rounded, dynamic, modern, elaborate, unique, bright, pure, and clear. 'Jam' has a negative effect on consumer satisfaction. It means, consumer prefer the emotion which is empty, plain, and simple. Regulatory focus shows differences in motivation and propensity in various domains. It is important to consider organizational behavior and decision making according to the regulatory focus tendency, and it affects not only political, cultural, ethical judgments and behavior but also broad psychological problems. Regulatory focus also differs from emotional response. Promotion focus responds more strongly to positive emotional responses. On the other hand, prevention focus has a strong response to negative emotions. Web style is a type of service, and consumer satisfaction is affected not only by cognitive evaluation but also by emotion. This emotional response depends on whether the consumer will benefit or harm himself. Therefore, it is necessary to confirm the difference of the consumer's emotional response according to the regulatory focus which is one of the characteristics and viewpoint of the consumers about the web style. After MMR analysis result, hypothesis 5.3 was accepted, and hypothesis 5.4 was rejected. But hypothesis 5.4 supported in the opposite direction to the hypothesis. After validation, we confirmed the mechanism of emotional response according to the tendency of regulatory focus. Using the results, we developed the structure of web-style recommendation system and recommend methods through regulatory focus. We classified the regulatory focus group in to three categories that promotion, grey, prevention. Then, we suggest web-style recommend method along the group. If we further develop this study, we expect that the existing regulatory focus theory can be extended not only to the motivational part but also to the emotional behavioral response according to the regulatory focus tendency. Moreover, we believe that it is possible to recommend web-style according to regulatory focus and emotional desire which consumers most prefer.

• The Journal of Society for e-Business Studies
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• v.16 no.4
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• pp.33-51
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• 2011

This research derived the influencing factors for employees' compliance with the information security policy in organizations on the basis of Neutralization Theory, Theory of Planned Behavior and Protection Motivation Theory. To empirically analyze the research model and the hypotheses, data were collected by conducting web survey, 194 of 207 questionnaires were available. The test of causal model was conducted by PLS. Reliability, validity and model fit were found to be statistically significant. the results of hypotheses tests showed that seven ones of eight hypotheses could be accepted. The theoretical implications of this study are as follows : 1) this study is expected to play a role of baseline for future research about employee compliance with the information security policy, 2) this study attempted interdisciplinary approach through combining psychology and information system security research, and 3) it suggested concrete operational definitions of influencing factors for information security policy compliance through comprehensive theoretical review. Also, this study has some practical implications. First, it can provide the guideline to support the successful execution of the strategic establishment for implement of information system security policies in organizations. Second, it is proved that the need for conducting education and training program suppressing employees. neutralization psychology to violate information security policy should be emphasized in the organizations.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.101-116
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• 2015

Recently, due to the development of smart devices and social media, vast amounts of information with the various forms were accumulated. Particularly, considerable research efforts are being directed towards analyzing unstructured big data to resolve various social problems. Accordingly, focus of data-driven decision-making is being moved from structured data analysis to unstructured one. Also, in the field of recommendation system, which is the typical area of data-driven decision-making, the need of using unstructured data has been steadily increased to improve system performance. Approaches to improve the performance of recommendation systems can be found in two aspects- improving algorithms and acquiring useful data with high quality. Traditionally, most efforts to improve the performance of recommendation system were made by the former approach, while the latter approach has not attracted much attention relatively. In this sense, efforts to utilize unstructured data from variable sources are very timely and necessary. Particularly, as the interests of users are directly connected with their needs, identifying the interests of the user through unstructured big data analysis can be a crew for improving performance of recommendation systems. In this sense, this study proposes the methodology of improving recommendation system by measuring interests of the user. Specially, this study proposes the method to quantify interests of the user by analyzing user's internet usage patterns, and to predict user's repurchase based upon the discovered preferences. There are two important modules in this study. The first module predicts repurchase probability of each category through analyzing users' purchase history. We include the first module to our research scope for comparing the accuracy of traditional purchase-based prediction model to our new model presented in the second module. This procedure extracts purchase history of users. The core part of our methodology is in the second module. This module extracts users' interests by analyzing news articles the users have read. The second module constructs a correspondence matrix between topics and news articles by performing topic modeling on real world news articles. And then, the module analyzes users' news access patterns and then constructs a correspondence matrix between articles and users. After that, by merging the results of the previous processes in the second module, we can obtain a correspondence matrix between users and topics. This matrix describes users' interests in a structured manner. Finally, by using the matrix, the second module builds a model for predicting repurchase probability of each category. In this paper, we also provide experimental results of our performance evaluation. The outline of data used our experiments is as follows. We acquired web transaction data of 5,000 panels from a company that is specialized to analyzing ranks of internet sites. At first we extracted 15,000 URLs of news articles published from July 2012 to June 2013 from the original data and we crawled main contents of the news articles. After that we selected 2,615 users who have read at least one of the extracted news articles. Among the 2,615 users, we discovered that the number of target users who purchase at least one items from our target shopping mall 'G' is 359. In the experiments, we analyzed purchase history and news access records of the 359 internet users. From the performance evaluation, we found that our prediction model using both users' interests and purchase history outperforms a prediction model using only users' purchase history from a view point of misclassification ratio. In detail, our model outperformed the traditional one in appliance, beauty, computer, culture, digital, fashion, and sports categories when artificial neural network based models were used. Similarly, our model outperformed the traditional one in beauty, computer, digital, fashion, food, and furniture categories when decision tree based models were used although the improvement is very small.

• Composites Research
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• v.15 no.6
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• pp.38-43
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• 2002

Rapid Prototyping(RP) technologies provide the ability to fabricate initial prototypes from various model materials. Stratasys' Fused Deposition Modeling(FDM) is a typical RP process that can fabricate prototypes out of plastic materials, and the parts made from FDM were often used as load-carrying elements. Because FDM deposits materials in about 300$\mu$m thin filament with designated orientation, parts made from FDM show anisotropic material properties. In this paper an analytic model was proposed to predict the tensile strength of FDM parts. Applying the Classical Lamination Theory, which was developed for laminated composite materials, a computer code was implemented. Tsai-Wu failure criterion was added to the code to predict the failure of the FDM parts. The tensile strengths predicted by the analytic model were compared with experimental data. The data and prediction agreed reasonably well to prove the validity of the model. In addition, a web-based advisory service(FDMAS) was developed to provide strength prediction and design rules for FDM parts.

• Journal of The Korean Association of Information Education
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• v.8 no.2
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• pp.167-176
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• 2004

Due to the development of information communication technology, educational environment has undergone much change and various types of teaching and learning methods based on information communication technology has been suggested. Recently, remote education using the internet are also spreading. However, in current classrooms, students are asked to do an teacher-centered assignment, which they are required to collect and report some information using the internet. This method does not help students use the advantages of learning using the internet, which stimulate students-students interaction and teacher-students interaction.Thus, this study focused on the problem-based learning system based on video communication technology. The researcher designed the problem-based learning system based on video communication technology and applied the system to classes at elementary school. The results were analyzed in terms of students-students interaction and teacher-students interaction in the internet. This research found that the problem-based learning system stimulates teacher and students communication and has positive effects on students' attitude and interest in learning. This research proposes that the traditional teacher-centered teaching method can be supplemented with cyber space learning, which has the merit of problem-based learning model.

• Journal of The Korean Association of Information Education
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• v.8 no.1
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• pp.67-77
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• 2004

Recently, the rapid progress of internet technology stirs the widespread development in the educational areas. Internet has been exploited as an effective means to support school information management as well as to supplement traditional off-line teaching-learning methods. Science instruments are very important tools for science-related courses in the elementary schools. However, managing science instruments effectively has not been concerned greatly so far. Only off-line management systems were presented. In this paper, a Web-based science instrument management system is proposed. The proposed Web-based science instrument management system has the following characteristics. First, an extensive model for science instrument management is presented. The proposed model can be used as a standard model for effective management. Second, the system can provide inventory information as well as standard instrument requirements to teachers anytime anywhere. The system helps teachers make decisions on procurement plan. Finally, the user interface is designed to support easy navigation and simple use.

• Journal of Environmental Impact Assessment
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• v.10 no.3
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• pp.235-243
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• 2001

Since the middle of 1990s, in Korea a few researches on the optimal management technologies combining numerical model and GIS for the management of water environment in drinking watershed area and reservoir such as Paldang Lake have been carried out. In this study, the integrated water environment management system was been suggested to efficiently reflect the public awareness of the environment by integrating the web based distributed data collection system, GIS, public hearing system and water quality model. As all the components of the system have been developed using the World Wide Web and all data have been collected from the relevant agencies through the Internet, the water quality model could be implemented on the web directly. In consequence, the environmental geographic information in Paldang Lake could be acquired and analyzed through the Internet. The system can rapidly respond to the public right to know on environment, so the public will willingly participate in the governmental projects on environment. To verify the usability of the developed system, it has been applied to Paldang Lake. Especially when the web based model has been used, users can easily and confidentially get the prediction results by applying the minimum number of parameters for the water quality model. This model will provide clearness and scientific bases in the process of water quality prediction for the sensitive sites where there are critical conflicts between the residents and the developers. In this study, rapid water environment management technique without spatial and time limit has been suggested, which can contribute to the efforts on the government and the public participation.

• 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 Korea Society of Computer and Information
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• v.28 no.7
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• pp.29-37
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• 2023

Due to climate change, interest in crop production and distribution is increasing, and attempts are being made to use bigdata and AI to predict production volume and control shipments and distribution stages. Prediction of agricultural product imports not only affects prices, but also controls shipments of farms and distributions of distribution companies, so it is important information for establishing marketing strategies. In this paper, we create an artificial intelligence prediction model that predicts the future import volume based on the wholesale market melon import volume data disclosed by the agricultural statistics information system and evaluate its accuracy. We create prediction models using three models: the Neural Prophet technique, the Ensembled Neural Prophet model, and the GRU model. As a result of evaluating the performance of the model by comparing two major indicators, MAE and RMSE, the Ensembled Neural Prophet model predicted the most accurately, and the GRU model also showed similar performance to the ensemble model. The model developed in this study is published on the web and used in the field for 1 year and 6 months, and is used to predict melon production in the near future and to establish marketing and distribution strategies.