• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.99-122
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• 2019

According to the recent IDC (International Data Corporation) report, as from 2025, the total volume of data is estimated to reach ten times higher than that of 2016, corresponding to 163 zettabytes. then the main body of generating information is moving more toward corporations than consumers. So-called "the wave of Big-data" is arriving, and the following aftermath affects entire industries and firms, respectively and collectively. Therefore, effective management of vast amounts of data is more important than ever in terms of the firm. However, there have been no previous studies that measure the effects of big data investment, even though there are number of previous studies that quantitatively the effects of IT investment. Therefore, we quantitatively analyze the Big-data investment effects, which assists firm's investment decision making. This study applied the Event Study Methodology, which is based on the efficient market hypothesis as the theoretical basis, to measure the effect of the big data investment of firms on the response of market investors. In addition, five sub-variables were set to analyze this effect in more depth: the contents are firm size classification, industry classification (finance and ICT), investment completion classification, and vendor existence classification. To measure the impact of Big data investment announcements, Data from 91 announcements from 2010 to 2017 were used as data, and the effect of investment was more empirically observed by observing changes in corporate value immediately after the disclosure. This study collected data on Big Data Investment related to Naver 's' News' category, the largest portal site in Korea. In addition, when selecting the target companies, we extracted the disclosures of listed companies in the KOSPI and KOSDAQ market. During the collection process, the search keywords were searched through the keywords 'Big data construction', 'Big data introduction', 'Big data investment', 'Big data order', and 'Big data development'. The results of the empirically proved analysis are as follows. First, we found that the market value of 91 publicly listed firms, who announced Big-data investment, increased by 0.92%. In particular, we can see that the market value of finance firms, non-ICT firms, small-cap firms are significantly increased. This result can be interpreted as the market investors perceive positively the big data investment of the enterprise, allowing market investors to better understand the company's big data investment. Second, statistical demonstration that the market value of financial firms and non - ICT firms increases after Big data investment announcement is proved statistically. Third, this study measured the effect of big data investment by dividing by company size and classified it into the top 30% and the bottom 30% of company size standard (market capitalization) without measuring the median value. To maximize the difference. The analysis showed that the investment effect of small sample companies was greater, and the difference between the two groups was also clear. Fourth, one of the most significant features of this study is that the Big Data Investment announcements are classified and structured according to vendor status. We have shown that the investment effect of a group with vendor involvement (with or without a vendor) is very large, indicating that market investors are very positive about the involvement of big data specialist vendors. Lastly but not least, it is also interesting that market investors are evaluating investment more positively at the time of the Big data Investment announcement, which is scheduled to be built rather than completed. Applying this to the industry, it would be effective for a company to make a disclosure when it decided to invest in big data in terms of increasing the market value. Our study has an academic implication, as prior research looked for the impact of Big-data investment has been nonexistent. This study also has a practical implication in that it can be a practical reference material for business decision makers considering big data investment.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.197-217
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• 2018

Music is one of the most creative act that can express human sentiment with sound. Also, since music invoke people's sentiment to get empathized with it easily, it can either encourage or discourage people's sentiment with music what they are listening. Thus, sentiment is the primary factor when it comes to searching or recommending music to people. Regard to the music recommendation system, there are still lack of recommendation systems that are based on customer sentiment. An algorithm's that were used in previous music recommendation systems are mostly user based, for example, user's play history and playlists etc. Based on play history or playlists between multiple users, distance between music were calculated refer to basic information such as genre, singer, beat etc. It can filter out similar music to the users as a recommendation system. However those methodology have limitations like filter bubble. For example, if user listen to rock music only, it would be hard to get hip-hop or R&B music which have similar sentiment as a recommendation. In this study, we have focused on sentiment of music itself, and finally developed methodology of defining new index for music recommendation system. Concretely, we are proposing "SWEMS" index and using this index, we also extracted "Sentiment Pattern" for each music which was used for this research. Using this "SWEMS" index and "Sentiment Pattern", we expect that it can be used for a variety of purposes not only the music recommendation system but also as an algorithm which used for buildup predicting model etc. In this study, we had to develop the music recommendation system based on emotional adjectives which people generally feel when they listening to music. For that reason, it was necessary to collect a large amount of emotional adjectives as we can. Emotional adjectives were collected via previous study which is related to them. Also more emotional adjectives has collected via social metrics and qualitative interview. Finally, we could collect 134 individual adjectives. Through several steps, the collected adjectives were selected as the final 60 adjectives. Based on the final adjectives, music survey has taken as each item to evaluated the sentiment of a song. Surveys were taken by expert panels who like to listen to music. During the survey, all survey questions were based on emotional adjectives, no other information were collected. The music which evaluated from the previous step is divided into popular and unpopular songs, and the most relevant variables were derived from the popularity of music. The derived variables were reclassified through factor analysis and assigned a weight to the adjectives which belongs to the factor. We define the extracted factors as "SWEMS" index, which describes sentiment score of music in numeric value. In this study, we attempted to apply Case Based Reasoning method to implement an algorithm. Compare to other methodology, we used Case Based Reasoning because it shows similar problem solving method as what human do. Using "SWEMS" index of each music, an algorithm will be implemented based on the Euclidean distance to recommend a song similar to the emotion value which given by the factor for each music. Also, using "SWEMS" index, we can also draw "Sentiment Pattern" for each song. In this study, we found that the song which gives a similar emotion shows similar "Sentiment Pattern" each other. Through "Sentiment Pattern", we could also suggest a new group of music, which is different from the previous format of genre. This research would help people to quantify qualitative data. Also the algorithms can be used to quantify the content itself, which would help users to search the similar content more quickly.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.33-49
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• 2018

The impact of TV Drama success on TV Rating and the channel promotion effectiveness is very high. The cultural and business impact has been also demonstrated through the Korean Wave. Therefore, the early prediction of the blockbuster success of TV Drama is very important from the strategic perspective of the media industry. Previous studies have tried to predict the audience ratings and success of drama based on various methods. However, most of the studies have made simple predictions using intuitive methods such as the main actor and time zone. These studies have limitations in predicting. In this study, we propose a model for predicting the popularity of drama by analyzing the customer's viewing pattern based on various theories. This is not only a theoretical contribution but also has a contribution from the practical point of view that can be used in actual broadcasting companies. In this study, we collected data of 280 TV mini-series dramas, broadcasted over the terrestrial channels for 10 years from 2003 to 2012. From the data, we selected the most highly ranked and the least highly ranked 45 TV drama and analyzed the viewing patterns of them by 11-step. The various assumptions and conditions for modeling are based on existing studies, or by the opinions of actual broadcasters and by data mining techniques. Then, we developed a prediction model by measuring the viewing-time distance (difference) using Euclidean and Correlation method, which is termed in our study similarity (the sum of distance). Through the similarity measure, we predicted the success of dramas from the viewer's initial viewing-time pattern distribution using 1~5 episodes. In order to confirm that the model is shaken according to the measurement method, various distance measurement methods were applied and the model was checked for its dryness. And when the model was established, we could make a more predictive model using a grid search. Furthermore, we classified the viewers who had watched TV drama more than 70% of the total airtime as the "passionate viewer" when a new drama is broadcasted. Then we compared the drama's passionate viewer percentage the most highly ranked and the least highly ranked dramas. So that we can determine the possibility of blockbuster TV mini-series. We find that the initial viewing-time pattern is the key factor for the prediction of blockbuster dramas. From our model, block-buster dramas were correctly classified with the 75.47% accuracy with the initial viewing-time pattern analysis. This paper shows high prediction rate while suggesting audience rating method different from existing ones. Currently, broadcasters rely heavily on some famous actors called so-called star systems, so they are in more severe competition than ever due to rising production costs of broadcasting programs, long-term recession, aggressive investment in comprehensive programming channels and large corporations. Everyone is in a financially difficult situation. The basic revenue model of these broadcasters is advertising, and the execution of advertising is based on audience rating as a basic index. In the drama, there is uncertainty in the drama market that it is difficult to forecast the demand due to the nature of the commodity, while the drama market has a high financial contribution in the success of various contents of the broadcasting company. Therefore, to minimize the risk of failure. Thus, by analyzing the distribution of the first-time viewing time, it can be a practical help to establish a response strategy (organization/ marketing/story change, etc.) of the related company. Also, in this paper, we found that the behavior of the audience is crucial to the success of the program. In this paper, we define TV viewing as a measure of how enthusiastically watching TV is watched. We can predict the success of the program successfully by calculating the loyalty of the customer with the hot blood. This way of calculating loyalty can also be used to calculate loyalty to various platforms. It can also be used for marketing programs such as highlights, script previews, making movies, characters, games, and other marketing projects.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.239-251
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• 2019

Statistical methods such as moving averages, Kalman filtering, exponential smoothing, regression analysis, and ARIMA (autoregressive integrated moving average) have been used for stock market predictions. However, these statistical methods have not produced superior performances. In recent years, machine learning techniques have been widely used in stock market predictions, including artificial neural network, SVM, and genetic algorithm. In particular, a case-based reasoning method, known as k-nearest neighbor is also widely used for stock price prediction. Case based reasoning retrieves several similar cases from previous cases when a new problem occurs, and combines the class labels of similar cases to create a classification for the new problem. However, case based reasoning has some problems. First, case based reasoning has a tendency to search for a fixed number of neighbors in the observation space and always selects the same number of neighbors rather than the best similar neighbors for the target case. So, case based reasoning may have to take into account more cases even when there are fewer cases applicable depending on the subject. Second, case based reasoning may select neighbors that are far away from the target case. Thus, case based reasoning does not guarantee an optimal pseudo-neighborhood for various target cases, and the predictability can be degraded due to a deviation from the desired similar neighbor. This paper examines how the size of learning data affects stock price predictability through k-nearest neighbor and compares the predictability of k-nearest neighbor with the random walk model according to the size of the learning data and the number of neighbors. In this study, Samsung electronics stock prices were predicted by dividing the learning dataset into two types. For the prediction of next day's closing price, we used four variables: opening value, daily high, daily low, and daily close. In the first experiment, data from January 1, 2000 to December 31, 2017 were used for the learning process. In the second experiment, data from January 1, 2015 to December 31, 2017 were used for the learning process. The test data is from January 1, 2018 to August 31, 2018 for both experiments. We compared the performance of k-NN with the random walk model using the two learning dataset. The mean absolute percentage error (MAPE) was 1.3497 for the random walk model and 1.3570 for the k-NN for the first experiment when the learning data was small. However, the mean absolute percentage error (MAPE) for the random walk model was 1.3497 and the k-NN was 1.2928 for the second experiment when the learning data was large. These results show that the prediction power when more learning data are used is higher than when less learning data are used. Also, this paper shows that k-NN generally produces a better predictive power than random walk model for larger learning datasets and does not when the learning dataset is relatively small. Future studies need to consider macroeconomic variables related to stock price forecasting including opening price, low price, high price, and closing price. Also, to produce better results, it is recommended that the k-nearest neighbor needs to find nearest neighbors using the second step filtering method considering fundamental economic variables as well as a sufficient amount of learning data.

• Korean Journal of Heritage: History & Science
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• v.37
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• pp.121-150
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• 2004

As genre of Buddhist paintings that express generally mountains and waters, there are Eight Scenes from Life of the Buddha(八相圖), Eternal Life Painting(甘露圖), Avalokitesvara Painting(觀音菩薩圖) includes Sixteen Lohans painting(十六羅漢圖), and Hermit Painting(獨聖圖), or Mountain God Painting(山神圖) which is especially appeared in late Chosun Period. These Buddhist paintings had various backgrounds including mountains and waters, the tradition of Water Ink Painting still remains after 18th century, however the trends got complicated to express various landscapes including splendid color, waters and mountains, and it appeared to have historical trend with introduction of factors of Minhwa(民畵) so called in 19th century. Sixteen Lohans painting painted from late 19th to early 20th century, still contains the traditional factors in terms of describing background among above trends, however the main factors of expressing the background are different from other Buddhist painting which reflects historical art trends in colors and its materials by drawing various background distinctively. That is, Sixteen Lohans painting is distinct at describing the background of blue & green colored mountains and waters that is appeared in trend of Minhwa(民畵) and the royal which were popular at that time It also shows broad acceptance with introduction of new background expressions such as Sipjangsang(十長生, Picture of 10 different things of Sun, Mountain, Water, Stone, Cloud, Pine, Plant of eternal youth, tortoise, Crane, and deer to hope the eternal life) Unryoung(雲龍, Dragon Cloud), Mangho(猛虎, Wild Tiger), Gweseck(怪石, Oddly shaped stone), Hwajo(花鳥, Flowers and Birds), Chaekgoeri(冊巨里, The books and bookshaves). In terms of its materials, positive representations of eternal life, wealth and luck were mainly appeared, this is closely related with Self-Search of Buddhist which was the trend at that time that Buddhist turned into the popularized religion in Chosun Period, especially the cooperation of popular belief with Taoism. This is appeared on various Taoists that is expressed in Buddhist paintings of Sixteen Lohans painting at that time. It would provide some clauses to infer the painted years of existing Minhwa at the fixed type of folk story paintings appeared on Sixteen Lohans painting painted mainly from late 19th to early 20th Century. There is also a possibility of the active participation of Buddhist painters(佛畵僧) as painters of Minhwa by request and demands from common people. Inquiry into factors of folk story paintings among Buddhist paintings started from similarity of the materials and shapes, however it doesn't seem to have dramatically expressed comic or exceptional techniques. But, the fact that there are similar types of decorative pictures in the Royal Court rather seemed to be possible for Buddhist paintings to have functions as religion.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.1
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• pp.40-53
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• 2021

Research vessels(R/Vs) used for ocean research move to the planned research area and perform ocean observations suitable for the research purpose. The five research vessels of the Korea Institute of Ocean Science & Technology(KIOST) are equipped with global positioning system(GPS), water depth, weather, sea surface layer temperature and salinity measurement equipment that can be observed at all times during cruise. An information platform is required to systematically manage and utilize the data produced through such continuous observation equipment. Therefore, the data flow was defined through a series of business analysis ranging from the research vessel operation plan to observation during the operation of the research vessel, data collection, data processing, data storage, display and service. After creating a functional design for each stage of the business process, KIOST Underway Meteorological & Oceanographic Information System(KUMOS), a Web-Geographic information system (Web-GIS) based information platform, was built. Since the data produced during the cruise of the R/Vs have characteristics of temporal and spatial variability, a quality management system was developed that considered these variabilities. For the systematic management and service of data, the KUMOS integrated Database(DB) was established, and functions such as R/V tracking, data display, search and provision were implemented. The dataset provided by KUMOS consists of cruise report, raw data, Quality Control(QC) flagged data, filtered data, cruise track line data, and data report for each cruise of the R/V. The business processing procedure and system of KUMOS for each function developed through this study are expected to serve as a benchmark for domestic ocean-related institutions and universities that have research vessels capable of continuous observations during cruise.

• Journal of Ginseng Culture
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• v.4
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• pp.13-37
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• 2022

Even before recorded history, the Korean people took ginseng. Later, poetry passed down from China developed into a literary style in which intellectuals from the Silla, Goryeo, and Joseon Dynasties expressed their thoughts concisely. The aim of this paper is to find Korean poems related to ginseng and to look for their semantic network. To this end, "Korea Classical DB ", produced by the Institute for the Translation of Korean Classics, was searched to find ginseng poems. As the result of a search in November 2021, two poems from the Three Kingdoms Period, two poems from the Goryeo Dynasty, and 23 poems from the Joseon Dynasty were searched. An examination of these poems found that the first ginseng poem was "Goryeoinsamchan," which was sung by people in Goguryeo around the 6th century. Ginseng poetry during the Goryeo Dynasty is represented by Anchuk's poem. Anchuk sang about the harmful effects of ginseng tributes from a realistic point of view. Ginseng poetry in the Joseon Dynasty is represented by Seo Geo-jeong in the early period and Jeong Yakyong in the late period. Seo Geo-jeong's ginseng poem is a romantic poem that praises the mysterious pharmacological effects of ginseng. A poem called "Ginseng" by Yongjae Seonghyeon is also a romantic poem that praises the mysterious medicinal benefits of ginseng. As a scholar of Realist Confucianism, Dasan Jeong Yak-yong wrote very practical ginseng poems. Dasan left five ginseng poems, the largest number written by one poet. Dasan tried ginseng farming himself and emerged from the experience as a poet. The story of the failure and success of his ginseng farming was described in his poems. At that time, ginseng farming was widespread throughout the country due to the depletion of natural ginseng and the development of ginseng farming techniques after the reign of King Jeongjo. Since the early 19th century, ginseng farming had been prevalent on a large scale in the Gaeseong region, and small-scale farming had also been carried out in other regions. What is unusual is Kim Jin-soo's poem. At that time, in Tong Ren Tang, Beijing (the capital of the Qing Dynasty), ginseng from Joseon sold well under the "Songak Sansam" brand. Kim Jin-Soo wrote about this brand of ginseng in his poem. In 1900, Maecheon Hwanghyeon also created a ginseng poem, written in Chinese characters. Thus, the semantic network of Korean ginseng poems is identified as follows: 1) Ginseng poetry in the spirit of the people - Emerging gentry in the Goryeo Dynasty (Anchuk). 2) Romantic ginseng poetry - Government School in the early Joseon Dynasty (Seo Geo-jeong, Seonghyeon, etc.). 3) Practical ginseng poetry - Realist School in the late Joseon Dynasty (Jeong Yak-yong, Kim Jin-soo, Hwang Hyun, etc.). This semantic network was extracted while examining the development of Korean ginseng poems.

• Journal of Korean Home Economics Education Association
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• v.33 no.1
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• pp.17-35
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• 2021

The purpose of this study is to derive implications for the development of the next home economics curriculum by comparing the 'function' and 'achievement standard' presented in the 14 subjects of the 2015 revised middle school common curriculum with the home economics curriculum. For this, keyword network analysis was conducted, and the results are as follows. First, in the 'function' of the 2015 revised middle school common curriculum, 'analysis, use, and expression' were found to be core function keywords with high Degree Centrality and the Eigenvector Centrality. Second, the functional keywords 'understanding, explanation, expression, analysis, and use' in the 'achievement standard' of the 2015 revised middle school common curriculum appeared with high frequency, and 'practice, problem-solving, search and reasoning' which are related to practical problem-solving ability appeared. It was confirmed that 'appreciation, solution and realization', which have relatively high Eigenvector Centrality, were core functional keywords used in the 'achievement standard'. Third, when the 'function' and 'achievement standard' of the 2015 revised middle school home economics curriculum were matched and compared, 7 out of 15 functions were not used in the statement of 'achievement standard', so the connection between 'function' and 'achievement standard' appeared to be insufficient. In addition, the diversity of functional keyword used in the 'achievement standard' was also found insufficient when compared to the middle school common curriculum. Therefore, this study propose strengthening the connectivity of 'function' and 'achievement standard' in the next home economics curriculum, using keywords such as 'analyze', 'express', 'compare', 'understand', 'interpret', 'explore', 'appreciate', and 'solve'.

• Journal of Korea Entertainment Industry Association
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• v.14 no.6
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• pp.53-60
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• 2020

The study is based on the assumption that the trend of phenomena and trends in research are contextually consistent. Therefore the purpose of this study is to explore the trend of dance through the subject analysis of the Korean creative dance study by utilizing text mining. Thus, 1,291 words were analyzed in the 616 journal title, which were established on the paper search website. The collection, refining and analysis of the data were all R 3.6.0 SW. According to the study, keywords representing the times were frequently used before the 2000s, but Korean creative dance research types were also found in terms of education and physical training. Second, the frequency of keywords related to the dance troupe's performance was high after the 2000s, but it was confirmed that Choi Seung-hee was still in an important position in the study of Korean creative dance. Third, an analysis of the overall research subjects of the Korean creative dance study showed that the research on 'Art of Choi Seung-hee in the modern era' was the highest proportion. Fourth, the Hot Topics, which are rising as of 2000, appeared as 'the performance activities of the National Dance Company' and 'the choreography expression and utilization of traditional dance'. However, since the recent trend of the National Dance Company's performance is advocating 'modernization based on tradition', it has been confirmed that the trend of Korean creative dance since the 2000s has been focused on the use of traditional dance motifs. Fifth, the Cold Topic, which has been falling as of 2000, has been shown to be a study of 'dancing expressions by age'. It was judged that interest in research also decreased due to the tendency to mix various dance styles after the establishment of the genre of Korean creative dance.

• Journal of the Korean Association of African Studies
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• v.29
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• pp.27-53
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• 2009

At the start of the new century, South Africa probably had the largest number of HIV-infected people of any country in the world. The only nation that comes close is India with a population of one billion people compared to South Africa's figure of 57 million. The tragedy is that this did not have to happen. South Africa was aware of the dangers posed by AIDS as early as 1985. In 1991, the national survey of women attending antenatal clinics found that only 0.8percent were infected. In 1994, when the new government took power, the figure was still comparatively low at 7.6 %. The 2004 figure which has been published is 26.5%. This article tracks the epidemic globally, in the region and in South Africa. I explain some of the basic concepts around the disease and look at what may happen with respect to numbers. The situation is bad, and the number of people falling ill, dying and leaving families will rise over next few years. This will impact on South Africa in a number of important ways. This article assesses the demographic, economic and social consequences of the epidemic. It disposes of a number of myths and present the real facts. The AIDS in South Africa is not related to individuals only. It warns that AIDS in Africa is becoming a community and systemic problem. The acuteness of the problem does not stem merely from the fact that communities are affected, or could even be wipe out by the end of this decade, but from the fact that AIDS will place incredible burdens and obligations upon medical services, health care and religious communities such as churches. The facts confront churches' mission with the important question: who is going to take care of all the patients and where? The reality is that people dying of AIDS will have to be cared for at home by relatives and friends. A further question that arises is whether our people are prepared for this. AIDS was considered to be a homo-plague and the hunt was on for a scapegoat in the light of the fatal implication of the disease. At present we are in the strategic phase where we all realize that it will be of no avail to scare people with the ominous threat of AIDS AIDS destroys the optimism of our achievement ethics. This exposure of the culture of optimism is also an exposure of the so-called 'human basic fear which accuses Christianity that their concept of sin is a damper on man's search for liberation and basic need to be freed from all Imitation. AIDS is also a test for our ecclesiastical genuineness and the sincerity of our mission sensibility. It poses the question: How unconditional is Christian love? Is there room for the AIDS sufferer in the community of believers, despite the fact he is an acknowledged homosexual? The question to put to the church is whether the community of believers is an exclusive to put to the koinonia which excludes homosexuals. They may be welcome on principle, but in actual fact are not acceptable to the church community. As South Africa enters the new century, it is clear that the epidemic is not having a measurable impact. However, the impact of AIDS is gradual, subtle and incremental. The author's proposal of what is currently most needed in South Africa is that the little things will make a difference. It's about doing lots of little things better at grassroots level, with the emphasis on doing. There are so many community, churches and NGOs initiatives worth building on and intensifying. One must not underestimate the therapeutic value of working together in small groups to overcome a problem