• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.77-97
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• 2019

The large amount of data that emerges from the initial connection environment of the Fourth Industrial Revolution is a major factor that distinguishes the Fourth Industrial Revolution from the existing production environment. This environment has two-sided features that allow it to produce data while using it. And the data produced so produces another value. Due to the massive scale of data, future information systems need to process more data in terms of quantities than existing information systems. In addition, in terms of quality, only a large amount of data, Ability is required. In a small-scale information system, it is possible for a person to accurately understand the system and obtain the necessary information, but in a variety of complex systems where it is difficult to understand the system accurately, it becomes increasingly difficult to acquire the desired information. In other words, more accurate processing of large amounts of data has become a basic condition for future information systems. This problem related to the efficient performance of the information system can be solved by building a semantic web which enables various information processing by expressing the collected data as an ontology that can be understood by not only people but also computers. For example, as in most other organizations, IT has been introduced in the military, and most of the work has been done through information systems. Currently, most of the work is done through information systems. As existing systems contain increasingly large amounts of data, efforts are needed to make the system easier to use through its data utilization. An ontology-based system has a large data semantic network through connection with other systems, and has a wide range of databases that can be utilized, and has the advantage of searching more precisely and quickly through relationships between predefined concepts. In this paper, we propose a defense ontology as a method for effective data management and decision support. In order to judge the applicability and effectiveness of the actual system, we reconstructed the existing air force munitions situation management system as an ontology based system. It is a system constructed to strengthen management and control of logistics situation of commanders and practitioners by providing real - time information on maintenance and distribution situation as it becomes difficult to use complicated logistics information system with large amount of data. Although it is a method to take pre-specified necessary information from the existing logistics system and display it as a web page, it is also difficult to confirm this system except for a few specified items in advance, and it is also time-consuming to extend the additional function if necessary And it is a system composed of category type without search function. Therefore, it has a disadvantage that it can be easily utilized only when the system is well known as in the existing system. The ontology-based logistics situation management system is designed to provide the intuitive visualization of the complex information of the existing logistics information system through the ontology. In order to construct the logistics situation management system through the ontology, And the useful functions such as performance - based logistics support contract management and component dictionary are further identified and included in the ontology. In order to confirm whether the constructed ontology can be used for decision support, it is necessary to implement a meaningful analysis function such as calculation of the utilization rate of the aircraft, inquiry about performance-based military contract. Especially, in contrast to building ontology database in ontology study in the past, in this study, time series data which change value according to time such as the state of aircraft by date are constructed by ontology, and through the constructed ontology, It is confirmed that it is possible to calculate the utilization rate based on various criteria as well as the computable utilization rate. In addition, the data related to performance-based logistics contracts introduced as a new maintenance method of aircraft and other munitions can be inquired into various contents, and it is easy to calculate performance indexes used in performance-based logistics contract through reasoning and functions. Of course, we propose a new performance index that complements the limitations of the currently applied performance indicators, and calculate it through the ontology, confirming the possibility of using the constructed ontology. Finally, it is possible to calculate the failure rate or reliability of each component, including MTBF data of the selected fault-tolerant item based on the actual part consumption performance. The reliability of the mission and the reliability of the system are calculated. In order to confirm the usability of the constructed ontology-based logistics situation management system, the proposed system through the Technology Acceptance Model (TAM), which is a representative model for measuring the acceptability of the technology, is more useful and convenient than the existing system.

• 대한공업교육학회지
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• v.42 no.2
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• pp.1-19
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• 2017

The purpose of this study is to analyze the job performance hours and reasonable job performance hours of teachers working at secondary level technical vocational education institutes. This study analyzed the differences in the job performance hours and reasonable hours that have been investigated according to special subject teachers and general subject teachers. Based on Job Specifications of Teachers Working at Secondary Level Technical Vocational Education Institutes, the development of research tool was finalized, and questionnaires were used as the research tool. The results of this study are as follows. First, the total job performance hours and total reasonable job performance hours perceived by teachers working at secondary level technical vocational education institutes were found to be 2,787.8 minutes and 2,934.7 minutes respectively with a difference of 146.9 minutes. In regards to the job category-specific job performance hours, they were found to be high in the order of lesson administration, extracurricular student guidance, school affairs and administrative duties, and lesson preparation and planning, while the reasonable job performance hours were found to be high in the order of lesson administration, lesson preparation and planning, extracurricular student guidance, and school affairs and administrative duties. As for the job categories with shorter reasonable job performance hours compared to job performance hours, they were found to be lesson administration, extracurricular student guidance, and school affairs and administrative duties. In other job categories, it was found that longer job performance hours are needed. Second, the job performance hours perceived by each subject teacher from other schools, they were found to be 2,888.3 minutes for special subject teachers and 2,536.1 minutes for general subject teachers, while showing 3,021.8 minutes for special subject teachers and 2,716.8 minutes for general subject teachers regarding reasonable job performance hours. The differences between the job performance hours and reasonable job performance hours perceived by teachers from other schools were found to be 133.5 minutes for special subject teachers and 180.7 minutes for general subject teachers.

• The Journal of Industrial Distribution & Business
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• v.1 no.1
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• pp.5-12
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• 2010

The retail business of drugstore was introduced to Korea for the first time 10 years ago. Since Olive Young introduced a retail store in the name of drugstore in 1999 for the first time in Korea, new distribution channel combining drugstore, cosmetic products and dairy products, etc has been made. At initial stage, the new distribution channel grew up slowly because of low specialty and economic stagnation. However, the three big distribution channels, that is to say, Olive Young (CJ), Watsons (GS) and W Store (Kolon Well Care), etc, were established to produce new distribution system following large-scaled discount stores as well as convenience stores. The purpose of the study is to investigate ways making Korean style drugstore be new retail business in addition to traditional markets, department stores, E-Mart and other general super markets and to examine problems preventing the drugstore from being promoted and to find out solutions. The speciality retailers that is called a category killer attacking department stores as well as marts is expanding market quickly. New consumption trend that gives priority to wellbeing is being expanded in accordance with high level of standards of living life: The drugstore is thought to be new alternative of distribution because it keeps special products. Young ladies who are main customers of drugstores respond to the trend sensitively to have more buying power that is thought to be promising. And, consumers' desire has become concrete and special. This is because consumers want not only convenient shopping but also special shopping system that is current trend. These days, so called Multi-shop and Total shop and other special shops have been recently opened. Special multi-shop has been concentrated on fashion product and miscellaneous goods so far: Health total wellbeing shop shall be popular in accordance with wellbeing trends. Drugstores can play an important role. Drugstores were opened for the first time ten years ago. In particular, Olive Young succeeded in going into the black after making efforts for a long time by many persons. Drugstores could succeed in the business owing to many persons in the past as well as customers who liked drugstores. However, drugstores once lost ways and recorded poor business results. The three drugstores, that is to say, Olive Young, Watsons making efforts to go into the black and W-Store pursuing traditional drugstore shall compete each other and make effort to satisfy customers' desire. In that way, the three drugstores can be assured of present business as well as future business. The consumers' demand trend has become special at sub-division so that drugstores that can satisfy the demand can succeed in the business. Large businesses may be more interested in the 4th generation retail business to produce good income and to have bright future. Drugstore business and market are likely to expand and develop owing to large business' participation in drugstore business. Drugstores expanded shop at Seoul and Gyeonggi-do until middle of 2000. Drugstore business at station sphere in Seoul and Gyeonggi-do that have high ratio of temporary population has low customer loyalty to have limitation on continuous growth. Since 2009, drugstores have opened new shops at local towns: From the year of 2010, drugstores need to establish multiple shop strategy by accelerating business speed and to allow customers to drop in the shop anywhere in the nation and to enter consumers' life deeply, so that they can strengthen business base definitely. Drugstores need to have price competitiveness to have multiple shop opening strategy and to satisfy consumers and to supply high quality services that is future subject to solve. And, Olive Young and Watsons that are Korean style drugstore need to keep system in order and to strengthen substance as Korean style drugstore and to expand marketing, so that they can get business outcome within 5 years that was done 10 years before and they become the 4th generation retail business. The study had difficulties at collecting material from the three drugstore because of poor cooperation. And, the author had great difficulty at collecting statistical material that was made in disorder. Further effort is needed considering such problems.

• Journal of the Daesoon Academy of Sciences
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• v.35
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• pp.39-71
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• 2020

Ever since gaining liberation in 1945, Korean society has constantly recalled memories of Japan's invasion and Korea's anti-Japanese movements for an independent state (AMIS). In the process, a small number of new religious groups were also identified as main subjects within AMIS. However, the logic necessary to connect these religious groups with AMIS was still weak. In order to solve this situation academically, the purpose of this article is to illuminate the activities of Mugeukdo (無極道) and Jo Jeongsan (趙鼎山) through the lens of AMIS and to reflect on the issues that will arise when linking the religion with AMIS. Regarding this purpose, this article analyzed the internal and external data collected by Daesoon Jinrihoe (大巡眞理會) about Jo Jeongsan and Mugeukdo's activities linked to AMIS. Later, this paper presents several tasks for future research on this subject matter. Specifically, according to Chapter II, the AMIS of Jo Jeongsan and Mugeukdo were generally centered on resistance at the family level, Jo Jeongsan's order to participate in the March 1st Movement, and Mugeukdo's industrial activities. In Chapter III, I reviewed the contents of Chapter II using Daesoon Jinrihoe's external materials. According to the results of the review, future research is required to discover and cross-check materials related to the AMIS of Jo Jeongsan and Mugeukdo believers. Likewise, further research is needed to highlight the theory of the enthronement of emperor (天子登極說) and the Great Opening of the later world (後天開闢) in terms of AMIS. These efforts can make contributions that increase the credibility of Daesoon Jinrihoe's internal data on the AMIS of Jo Jeongsan and Mugeukdo and expand the periphery of AMIS as it relates to certain religious groups. Subsequently, in Chapter IV, I present three items for reflecting upon the connection between certain religious groups and AMIS. The first is that criteria for establishing the category of AMIS is necessary to determine whether religious activities can be included. Second, reductionist approaches make it difficult to explain the reasons why some of the people who participated in AMIS did so while forming 'new religious movements,' and why these groups have maintained their religious identity even after liberation was achieved in 1945. Third, it is necessary to distinguish between the primary and the secondary dimensions to elaborate on the connection between these religions and AMIS. This means that researchers should be expected to look at whether the activities in question are based on a religious worldview and whether the goal of the activities is the realization of AMIS or the implementation of some aspect of that religious worldview. In the future, considering the mechanisms that make AMIS memorable in Korea, religious groups and religious studies should take greater interest in discovering and accumulating data that facilitates research on these topics. At the same time, effort should be made to find the basis for AMIS within religious worldviews. It can also be made possible through specific interest in further elaboration on the various AMIS-related activities of Jo Jeongsan and Mugeukdo.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.123-138
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• 2017

Since the stock market is driven by the expectation of traders, studies have been conducted to predict stock price movements through analysis of various sources of text data. In order to predict stock price movements, research has been conducted not only on the relationship between text data and fluctuations in stock prices, but also on the trading stocks based on news articles and social media responses. Studies that predict the movements of stock prices have also applied classification algorithms with constructing term-document matrix in the same way as other text mining approaches. Because the document contains a lot of words, it is better to select words that contribute more for building a term-document matrix. Based on the frequency of words, words that show too little frequency or importance are removed. It also selects words according to their contribution by measuring the degree to which a word contributes to correctly classifying a document. The basic idea of constructing a term-document matrix was to collect all the documents to be analyzed and to select and use the words that have an influence on the classification. In this study, we analyze the documents for each individual item and select the words that are irrelevant for all categories as neutral words. We extract the words around the selected neutral word and use it to generate the term-document matrix. The neutral word itself starts with the idea that the stock movement is less related to the existence of the neutral words, and that the surrounding words of the neutral word are more likely to affect the stock price movements. And apply it to the algorithm that classifies the stock price fluctuations with the generated term-document matrix. In this study, we firstly removed stop words and selected neutral words for each stock. And we used a method to exclude words that are included in news articles for other stocks among the selected words. Through the online news portal, we collected four months of news articles on the top 10 market cap stocks. We split the news articles into 3 month news data as training data and apply the remaining one month news articles to the model to predict the stock price movements of the next day. We used SVM, Boosting and Random Forest for building models and predicting the movements of stock prices. The stock market opened for four months (2016/02/01 ~ 2016/05/31) for a total of 80 days, using the initial 60 days as a training set and the remaining 20 days as a test set. The proposed word - based algorithm in this study showed better classification performance than the word selection method based on sparsity. This study predicted stock price volatility by collecting and analyzing news articles of the top 10 stocks in market cap. We used the term - document matrix based classification model to estimate the stock price fluctuations and compared the performance of the existing sparse - based word extraction method and the suggested method of removing words from the term - document matrix. The suggested method differs from the word extraction method in that it uses not only the news articles for the corresponding stock but also other news items to determine the words to extract. In other words, it removed not only the words that appeared in all the increase and decrease but also the words that appeared common in the news for other stocks. When the prediction accuracy was compared, the suggested method showed higher accuracy. The limitation of this study is that the stock price prediction was set up to classify the rise and fall, and the experiment was conducted only for the top ten stocks. The 10 stocks used in the experiment do not represent the entire stock market. In addition, it is difficult to show the investment performance because stock price fluctuation and profit rate may be different. Therefore, it is necessary to study the research using more stocks and the yield prediction through trading simulation.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.17-35
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• 2015

Demand forecasting is the activity of estimating the quantity of a product or service that consumers will purchase for a certain period of time. Developing precise forecasting models are considered important since corporates can make strategic decisions on new markets based on future demand estimated by the models. Many studies have developed market growth curve models, such as Bass, Logistic, Gompertz models, which estimate future demand when a market is in its early stage. Among the models, Bass model, which explains the demand from two types of adopters, innovators and imitators, has been widely used in forecasting. Such models require sufficient demand observations to ensure qualified results. In the beginning of a new market, however, observations are not sufficient for the models to precisely estimate the market's future demand. For this reason, as an alternative, demands guessed from those of most adjacent markets are often used as references in such cases. Reference markets can be those whose products are developed with the same categorical technologies. A market's demand may be expected to have the similar pattern with that of a reference market in case the adoption pattern of a product in the market is determined mainly by the technology related to the product. However, such processes may not always ensure pleasing results because the similarity between markets depends on intuition and/or experience. There are two major drawbacks that human experts cannot effectively handle in this approach. One is the abundance of candidate reference markets to consider, and the other is the difficulty in calculating the similarity between markets. First, there can be too many markets to consider in selecting reference markets. Mostly, markets in the same category in an industrial hierarchy can be reference markets because they are usually based on the similar technologies. However, markets can be classified into different categories even if they are based on the same generic technologies. Therefore, markets in other categories also need to be considered as potential candidates. Next, even domain experts cannot consistently calculate the similarity between markets with their own qualitative standards. The inconsistency implies missing adjacent reference markets, which may lead to the imprecise estimation of future demand. Even though there are no missing reference markets, the new market's parameters can be hardly estimated from the reference markets without quantitative standards. For this reason, this study proposes a case-based expert system that helps experts overcome the drawbacks in discovering referential markets. First, this study proposes the use of Euclidean distance measure to calculate the similarity between markets. Based on their similarities, markets are grouped into clusters. Then, missing markets with the characteristics of the cluster are searched for. Potential candidate reference markets are extracted and recommended to users. After the iteration of these steps, definite reference markets are determined according to the user's selection among those candidates. Then, finally, the new market's parameters are estimated from the reference markets. For this procedure, two techniques are used in the model. One is clustering data mining technique, and the other content-based filtering of recommender systems. The proposed system implemented with those techniques can determine the most adjacent markets based on whether a user accepts candidate markets. Experiments were conducted to validate the usefulness of the system with five ICT experts involved. In the experiments, the experts were given the list of 16 ICT markets whose parameters to be estimated. For each of the markets, the experts estimated its parameters of growth curve models with intuition at first, and then with the system. The comparison of the experiments results show that the estimated parameters are closer when they use the system in comparison with the results when they guessed them without the system.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.167-194
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• 2019

This research starts from the four basic concepts of incentive incompatibility, limited information, myopia and decision variable which are confronted when making decisions in keyword bidding. In order to make these concept concrete, four framework approaches are designed as follows; Strategic approach for the incentive incompatibility, Statistical approach for the limited information, Alternative optimization for myopia, and New model approach for decision variable. The purpose of this research is to propose the statistical optimization model in constructing the portfolio of Sponsored Search Advertising (SSA) in the Sponsor's perspective through empirical tests which can be used in portfolio decision making. Previous research up to date formulates the CTR estimation model using CPC, Rank, Impression, CVR, etc., individually or collectively as the independent variables. However, many of the variables are not controllable in keyword bidding. Only CPC and Rank can be used as decision variables in the bidding system. Classical SSA model is designed on the basic assumption that the CPC is the decision variable and CTR is the response variable. However, this classical model has so many huddles in the estimation of CTR. The main problem is the uncertainty between CPC and Rank. In keyword bid, CPC is continuously fluctuating even at the same Rank. This uncertainty usually raises questions about the credibility of CTR, along with the practical management problems. Sponsors make decisions in keyword bids under the limited information, and the strategic portfolio approach based on statistical models is necessary. In order to solve the problem in Classical SSA model, the New SSA model frame is designed on the basic assumption that Rank is the decision variable. Rank is proposed as the best decision variable in predicting the CTR in many papers. Further, most of the search engine platforms provide the options and algorithms to make it possible to bid with Rank. Sponsors can participate in the keyword bidding with Rank. Therefore, this paper tries to test the validity of this new SSA model and the applicability to construct the optimal portfolio in keyword bidding. Research process is as follows; In order to perform the optimization analysis in constructing the keyword portfolio under the New SSA model, this study proposes the criteria for categorizing the keywords, selects the representing keywords for each category, shows the non-linearity relationship, screens the scenarios for CTR and CPC estimation, selects the best fit model through Goodness-of-Fit (GOF) test, formulates the optimization models, confirms the Spillover effects, and suggests the modified optimization model reflecting Spillover and some strategic recommendations. Tests of Optimization models using these CTR/CPC estimation models are empirically performed with the objective functions of (1) maximizing CTR (CTR optimization model) and of (2) maximizing expected profit reflecting CVR (namely, CVR optimization model). Both of the CTR and CVR optimization test result show that the suggested SSA model confirms the significant improvements and this model is valid in constructing the keyword portfolio using the CTR/CPC estimation models suggested in this study. However, one critical problem is found in the CVR optimization model. Important keywords are excluded from the keyword portfolio due to the myopia of the immediate low profit at present. In order to solve this problem, Markov Chain analysis is carried out and the concept of Core Transit Keyword (CTK) and Expected Opportunity Profit (EOP) are introduced. The Revised CVR Optimization model is proposed and is tested and shows validity in constructing the portfolio. Strategic guidelines and insights are as follows; Brand keywords are usually dominant in almost every aspects of CTR, CVR, the expected profit, etc. Now, it is found that the Generic keywords are the CTK and have the spillover potentials which might increase consumers awareness and lead them to Brand keyword. That's why the Generic keyword should be focused in the keyword bidding. The contribution of the thesis is to propose the novel SSA model based on Rank as decision variable, to propose to manage the keyword portfolio by categories according to the characteristics of keywords, to propose the statistical modelling and managing based on the Rank in constructing the keyword portfolio, and to perform empirical tests and propose a new strategic guidelines to focus on the CTK and to propose the modified CVR optimization objective function reflecting the spillover effect in stead of the previous expected profit models.