• Korean journal of communication and information
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• v.66
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• pp.59-86
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• 2014

This study explored how rumor is diffused via Twitter and how the characteristics of rumor affect the interactivity among users in the Korea-U.S. FTA case. A key word search located three issues as major ones related to the Korea-U.S. FTA: appendectomy myth, collapse of health insurance, and increases in medicine prices. The arousal of rumor has two dimensions: fact and expression. The fact arousal was the highest in the issue of 'appendectomy myth', and the expression arousal the highest in 'increases in medicine prices'. The rumor diffusion took the 'explosive wave' in the issue of appendectomy myth, the 'latent wave' in the issue of increase in medicine prices, and the 'repetitive wave' in the issue of collapse of health insurance. Correlation analyses revealed a high correlation between the arousal intensity of rumor and the user interactivity in the issue of collapse of health insurance. The study showed that Twitter took a role of diffusing negative messages about the Korea-U.S. FTA. Results implies that government officials and journalists pay attention to Twitter for sensing the public opinion when building policies and managing crises.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.15-28
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• 2015

As personal devices and pervasive technologies for interacting with networked objects continue to proliferate, there is an unprecedented world of scattered pieces of contextualized information available. However, the explosive growth and variety of information ironically lead users and service providers to make poor decision. In this situation, recommender systems may be a valuable alternative for dealing with these information overload. But they failed to utilize various types of contextual information. In this study, we suggest a methodology for context-aware recommender systems based on the concept of contextual boundary. First, as we suggest contextual boundary-based profiling which reflects contextual data with proper interpretation and structure, we attempt to solve complexity problem in context-aware recommender systems. Second, in neighbor formation with contextual information, our methodology can be expected to solve sparsity and cold-start problem in traditional recommender systems. Finally, we suggest a methodology about context support score-based recommendation generation. Consequently, our methodology can be first step for expanding application of researches on recommender systems. Moreover, as we suggest a flexible model with consideration of new technological development, it will show high performance regardless of their domains. Therefore, we expect that marketers or service providers can easily adopt according to their technical support.

• The Journal of the Korea Contents Association
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• v.22 no.9
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• pp.179-193
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• 2022

Amid the explosive growth of various metaverse platforms, there is no unified indicator to measure, analyze, and evaluate based on customer experience. Therefore, the usability evaluation factors in metaverse were identified through a heuristic methodology and literature review, to evaluate the metaverse, a two-to three-dimensional virtual world platform. A measurable system was established by subdividing 20 items in 5 fields, including user control, information structure, design and content, and usage environment, derived through Delphi technique. Based on this, after experiencing the actual contents of major metaverse platforms such as Roblox and Zepeto, usability was evaluated and comparative verification was conducted. As a result, it was estimated that metaverse user experience could be improved as its utility was derived relatively high in terms of user control and content. This study constitutes a theoretical contribution by extending the usability evaluation system, which has been widely used in the field of service design, to the fields of extended reality and mixed reality. At the same time, it has practical key findings of providing basic judgment standards to stakeholders in the metaverse field, as well as policy implications for digital capability enhancement and industry revitalization.

• Journal of Industrial Convergence
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• v.21 no.11
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• pp.1-12
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• 2023

With the recent explosive popularity of SNS, it is increasingly important to utilize SNS marketing, and in this process, the importance of image and caption order in SNS layout is also growing. This research aims to analyze the impact of SNS layouts (Image First vs. Caption First) on the user's attitude toward SNS shopping. A survey was conducted targeting 350 general public and college(graduate) students living in Daegu City and Gyeongbuk Province. The data was analyzed using PROCESS, regression analysis, and t-test by SPSS 21.0 program. The result of this study, it was confirmed that the Image First was more accessible than the Caption First. The Caption First was confirmed to be more diagnostic than the Image First. Moreover, from three specific mediation paths, only two were confirmed, named is through diagnosticity and usefulness, and through accessibility, diagnosticity, and usefullness. The path through diagnosticity and usefulness were stronger than another. Additionally, the impact of accessibility on diagnosticity was found to be higher when involvement was high rather than when involvement was low.

• Korean Security Journal
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• no.19
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• pp.105-138
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• 2009

This study's purpose is to present the improvement of effectiveness of security activity for international conference among Several Countries which can be held hereafter. On the basis of security activity problems originating in APEC that had been held in Busan in 2005. I made up questions three times to on the members of the police, military, fire figher and national intelligence service who had experienced in Busan APEC and recognition of possible problem and possibility of improvement on each item of questions was analyzed by Delphi Method. Also interviews with 4 security experts selected from each security agency were conducted to present improvement in each part of problem. The results obtained from the face to face interview with four experts of security-enforcement agency about the role and importance of site activity stage for international conference among several countries are as followings ; First, the system that experienced security-enforcement agents can be selected for the next national security event is needed, by data-basing the security-enforcement agents who were experienced in security event as man power management. Second, the middle-term plan for the introduction of high-tech equipment and joint inspection with relevant security agents are needed for the efficient explosive technical detection. Third, high-tech security equipment could be introduced through the international high-tech security equipment exhibition. Fourth, an anti-terrorism plan should be measured by sharing information through the cooperation with domestic and international intelligence agency. Fifth, public relations should be measured systematically by organization rather than agents' individual public relations. Sixth, political consideration to secure integrative coordination with other agency is needed for security activity, through normal cooperation with fire fighting related agency such as an electric, gas, elevator company. Seventh, a definite press guideline is needed for a convenient news coverage and safety during security event.

• The Korean Journal of Air & Space Law and Policy
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• v.1
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• pp.47-85
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• 1989

The Fundamental purpose of the Warsaw Convention was to establish uniform rules applicable to international air transportation. The emphasis on the benefits of uniformity was considered important in the beginning and continues to be important to the present. If the desire for uniformity is indeed the mortar which holds the Warsaw system together then it should be possible to agree on a worldwide liability limit. This liability limit would not be so unreasonable, that it would be impossible for nations to adhere to it. It would preclude any national supplemental compensation plan or Montreal Agreement type of requirement in any jurisdiction. The differentiation of liability limits by national requirement seems to be what is occurring. There is a plethora of mandated limits and Montreal Agreement type 'voluntary' limits. It is becoming difficult to find more than a few major States where an unmodified Warsaw Convention or Hague Protocol limitation is still in effect. If this is the real world in the 1980's, then let the treaty so reflect it. Upon reviewing the Warsaw Convention, its history and the several attempts to amend it, strengths become apparent. Hijackings of international flights have given rise to a number of lawsuits by passengers to recover damages for injuries suffered. This comment is concerned with the liability of an airline for injuries to its passengers resulting from aviation terrorism. In addition, analysis is focused on current airline security measures, particularly the pre-boarding screening system, and the duty of air carriers to prevent weapons from penetrating that system. An airline has a duty to exercise a high degree of care to protect its passengers from the threat of aviation terrorism. This duty would seemingly require the airline to exercise a high degree of care to prevent any passenger from smuggling a weapon or explosive device aboard its aircraft. In the case an unarmed hijacker who boards having no instrument in his possession with which to promote the hoax, a plaintiff-passenger would be hard-pressed to show that the airline was negligent in screening the hijacker prior to boarding. In light of the airline's duty to exercise a high degree of care to provide for the safety of all the passengers on board, an acquiescene to a hijacker's demands on the part of the air carrier could constitute a breach of duty only when it is clearly shown that the carrier's employees knew or plainly should have known that the hijacker was unarmed. A finding of willful misconduct on the part of an air carrier, which is a prerequisite to imposing unlimited liability, remains a question to be determined by a jury using the definition or standard of willful misconduct prevailing in the jurisdiction of the forum court. Through the willful misconduct provision of the Warsaw Convention, air carrier face the possibility of unlimited liability for failure to implement proper preventive precautions against terrorist. Courts, therefore, should broadly construe the willful misconduct provision of the Warsaw Convention in order to find unlimited liability for passenger injuries whenever air carrier security precautions are lacking. In this way, the courts can help ensure air carrier safety and prevention against terrorist attack. Air carriers, therefore, would have an incentive to increase, impose and maintain security precautions designed to thwart such potential terrorist attacks as in the case of Korean Air Lines Flight No.858 incident having a tremendous impact on the civil aviation community. The crash of a commercial airliner, with the attending tragic loss of life and massive destruction of property, always gives rise to shock and indignation. The general opinion is that the legal system could be sufficient, provided that the political will is there to use and apply it effectively. All agreed that the main responsibility for security has to be borne by the governments. I would like to remind all passengers that every discovery of the human spirit may be used for opposite ends; thus, aircraft can be used for air travel but also as targets of terrorism. A state that supports aviation terrorism is responsible for violation of International Aviation Law. Generally speaking, terrorism is a violation of international law. It violates the soverign rights of the states, and the human rights of the individuals. I think that aviation terrorism as becoming an ever more serious issue, has to be solved by internationally agreed and closely co-ordinated measures. We have to contribute more to the creation of a general consensus amongst all states about the need to combat the threat of aviation terrorism.

• The Journal of the Petrological Society of Korea
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• v.17 no.2
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• pp.57-82
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• 2008

The volcanic sequence of the late Cretaceous Moonyu volcanic mass which distributed in the southwestern part of Ryeongnam massif, can be divided into felsic pyroclastic rocks, andesite and andesitic pyroclastic rocks, rhyolite in ascending order. The earliest volcanic activity might commence with intermittent eruptions of felsic magma during deposition of volcaniclastic sediments. Explosive eruptions of felsic pyroclastic rocks began with ash-falls, to progressed through pumice-falls and transmitted with dacitic to rhyolitic ash-flows. Subsequent andesite and andesitic pyroclastic rocks were erupted and finally rhyolite was intruded as lava domes along the fractures near the center of volcanic mass. Petrochemical data show that these rocks are calc-alkaline series and have close petrotectonic affinities with subduction-related continental margin arc volcanic province. Major element compositions range from medium-K to high-K. Petrochemical variation within the volcanic sequence can be largely accounted for tractional crystallization processes with subordinate mixing. The most mafic rocks are basaltic andesite, but low MgO and Ni contents indicate they are fractionated by fractional crystallization from earlier primary mafic magma, which derived from less than 20% partial melting of ultramafic rocks in upper mantle wedge. Based on the stratigraphy, the early volcanic rocks are zoned from lower felsic to upper andesitic in composition. The compositional zonation of magma chamber from upper felsic to lower andesitic, is interpreted to have resulted from fractionation within the chamber and replenishment by an influx of new mafic magma from depth. Replenishment and mixing is based on observations of disequilibrium phenocrysts in volcanic rocks. REE patterns show slight enrichment of LREE with differentiation from andesite to rhyolite. Rhyolite in the final stage can be derived from calc-alkaline andesite magma by fractional crystallization, but it might have underwent crustal contamination during the fractional crystallization.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.119-142
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• 2015

With the explosive growth in the volume of information, Internet users are experiencing considerable difficulties in obtaining necessary information online. Against this backdrop, ever-greater importance is being placed on a recommender system that provides information catered to user preferences and tastes in an attempt to address issues associated with information overload. To this end, a number of techniques have been proposed, including content-based filtering (CBF), demographic filtering (DF) and collaborative filtering (CF). Among them, CBF and DF require external information and thus cannot be applied to a variety of domains. CF, on the other hand, is widely used since it is relatively free from the domain constraint. The CF technique is broadly classified into memory-based CF, model-based CF and hybrid CF. Model-based CF addresses the drawbacks of CF by considering the Bayesian model, clustering model or dependency network model. This filtering technique not only improves the sparsity and scalability issues but also boosts predictive performance. However, it involves expensive model-building and results in a tradeoff between performance and scalability. Such tradeoff is attributed to reduced coverage, which is a type of sparsity issues. In addition, expensive model-building may lead to performance instability since changes in the domain environment cannot be immediately incorporated into the model due to high costs involved. Cumulative changes in the domain environment that have failed to be reflected eventually undermine system performance. This study incorporates the Markov model of transition probabilities and the concept of fuzzy clustering with CBCF to propose predictive clustering-based CF (PCCF) that solves the issues of reduced coverage and of unstable performance. The method improves performance instability by tracking the changes in user preferences and bridging the gap between the static model and dynamic users. Furthermore, the issue of reduced coverage also improves by expanding the coverage based on transition probabilities and clustering probabilities. The proposed method consists of four processes. First, user preferences are normalized in preference clustering. Second, changes in user preferences are detected from review score entries during preference transition detection. Third, user propensities are normalized using patterns of changes (propensities) in user preferences in propensity clustering. Lastly, the preference prediction model is developed to predict user preferences for items during preference prediction. The proposed method has been validated by testing the robustness of performance instability and scalability-performance tradeoff. The initial test compared and analyzed the performance of individual recommender systems each enabled by IBCF, CBCF, ICFEC and PCCF under an environment where data sparsity had been minimized. The following test adjusted the optimal number of clusters in CBCF, ICFEC and PCCF for a comparative analysis of subsequent changes in the system performance. The test results revealed that the suggested method produced insignificant improvement in performance in comparison with the existing techniques. In addition, it failed to achieve significant improvement in the standard deviation that indicates the degree of data fluctuation. Notwithstanding, it resulted in marked improvement over the existing techniques in terms of range that indicates the level of performance fluctuation. The level of performance fluctuation before and after the model generation improved by 51.31% in the initial test. Then in the following test, there has been 36.05% improvement in the level of performance fluctuation driven by the changes in the number of clusters. This signifies that the proposed method, despite the slight performance improvement, clearly offers better performance stability compared to the existing techniques. Further research on this study will be directed toward enhancing the recommendation performance that failed to demonstrate significant improvement over the existing techniques. The future research will consider the introduction of a high-dimensional parameter-free clustering algorithm or deep learning-based model in order to improve performance in recommendations.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.

• Asia pacific journal of information systems
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• v.23 no.2
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• pp.1-20
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• 2013

Social commerce has been gaining explosive popularity, with typical examples of the model such as Groupon and Level Up. Both local business owners and consumers can benefit from this new e-commerce model. Local business owners have a chance to access potential customers and promote their products in a way that could not have otherwise been easily possible, and consumers can enjoy discounted offerings. However, questions have been increasingly raised about the value and future of the social commerce model. A recent survey shows that about a third of 324 business owners who ran a daily-deal promotion in Groupon went behind. Furthermore, more than half of the surveyed merchants did not express enthusiasm about running the promotion again. The same goes for the case in Korea, where more than half of the surveyed clients reported no significant change or even decrease in profits compared to before the use of social commerce model. Why do local business owners fail to exploit the benefits from the promotions and advertisements through the social commerce model and to make profits? Without answering this question, the model would fall under suspicion and even its sustainability might be challenged. This study aims to look into problems in the current social commerce transactions and provide implications for the social commerce model, so that the model would get a foothold for next growth. Drawing on justice theory, this study develops theoretical arguments for the effects of transaction characteristics on consumers' distributive justice and purchase intention in the social commerce. Specifically, this study focuses on two characteristics of social commerce transactions-the discount rate and the purchase rate of products-and investigates their effects on consumers' perception of distributive justice for discounted transactions in the social commerce and their perception of distributive justice for regular-priced transactions. This study also examines the relationship between distributive justice and purchase intention. We conducted an online experiment and gathered data from 115 participants to test the hypotheses. Each participant was randomly assigned to one of nine manipulated scenarios of social commerce transactions, which were generated based on the combination of three levels of purchase rate (high, medium, and low) and three levels of discount rate (high, medium, and low). We conducted MANOVA and post-hoc ANOVA to test hypotheses about the relationships between the transaction characteristics (purchase rate and discount rate) and distributive justice for each of the discounted transaction and the regular-priced transaction. We also employed a PLS analysis to test relations between distributive justice and purchase intentions. Analysis results show that a higher discount rate increases distributive justice for the discounted transaction but decreases distributive justice for the regular-priced transaction. This, coupled with the result that distributive justice for each type of transaction has a positive effect on the corresponding purchase intention, implies that a large discount in the social commerce may be helpful for attracting consumers, but harmful to the business after the promotion. However, further examination reveals curvilinear effects of the discount rate on both types of distributive justice. Specifically, we find distributive justice for the discounted transaction increases concavely as the discount rate increases while distributive justice for the regular-priced transaction decreases concavely with the dscount rate. This implies that there exists an appropriate discount rate which could promote the discounted transaction while not hurting future business of regular-priced transactions. Next, the purchase rate is found to be a critical factor that facilitates the regular-priced transaction. It has a convexly positive influence on distributive justice for the transaction. Therefore, an increase of the rate beyond some threshold would lead to a substantial level of distributive justice for the regular-priced transaction, threrby boosting future transactions. This implies that social commerce firms and sellers should employ various non-price stimuli to promote the purchase rate. Finally, we find no significant relationship between the purchase rate and distributive justice for the discounted transaction. Based on the above results, we provide several implications with future research directions.