• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.149-169
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• 2018

Korea is currently accumulating a large amount of data in public institutions based on the public data open policy and the "Government 3.0". Especially, a lot of data is accumulated in the tourism field. However, the academic discussions utilizing the tourism data are still limited. Moreover, the openness of the data of restaurants, hotels, and online tourism information, and how to use SNS Big Data in tourism are still limited. Therefore, utilization through tourism big data analysis is still low. In this paper, we tried to analyze influencing factors on foreign tourists' satisfaction in Korea through numerical data using data mining technique and R programming technique. In this study, we tried to find ways to revitalize the tourism industry by analyzing about 36,000 big data of the "Survey on the actual situation of foreign tourists from 2013 to 2015" surveyed by the Korea Culture & Tourism Research Institute. To do this, we analyzed the factors that have high influence on the 'Satisfaction', 'Revisit intention', and 'Recommendation' variables of foreign tourists. Furthermore, we analyzed the practical influences of the variables that are mentioned above. As a procedure of this study, we first integrated survey data of foreign tourists conducted by Korea Culture & Tourism Research Institute, which is stored in the tourist information system from 2013 to 2015, and eliminate unnecessary variables that are inconsistent with the research purpose among the integrated data. Some variables were modified to improve the accuracy of the analysis. And we analyzed the factors affecting the dependent variables by using data-mining methods: decision tree(C5.0, CART, CHAID, QUEST), artificial neural network, and logistic regression analysis of SPSS IBM Modeler 16.0. The seven variables that have the greatest effect on each dependent variable were derived. As a result of data analysis, it was found that seven major variables influencing 'overall satisfaction' were sightseeing spot attraction, food satisfaction, accommodation satisfaction, traffic satisfaction, guide service satisfaction, number of visiting places, and country. Variables that had a great influence appeared food satisfaction and sightseeing spot attraction. The seven variables that had the greatest influence on 'revisit intention' were the country, travel motivation, activity, food satisfaction, best activity, guide service satisfaction and sightseeing spot attraction. The most influential variables were food satisfaction and travel motivation for Korean style. Lastly, the seven variables that have the greatest influence on the 'recommendation intention' were the country, sightseeing spot attraction, number of visiting places, food satisfaction, activity, tour guide service satisfaction and cost. And then the variables that had the greatest influence were the country, sightseeing spot attraction, and food satisfaction. In addition, in order to grasp the influence of each independent variables more deeply, we used R programming to identify the influence of independent variables. As a result, it was found that the food satisfaction and sightseeing spot attraction were higher than other variables in overall satisfaction and had a greater effect than other influential variables. Revisit intention had a higher ${\beta}$ value in the travel motive as the purpose of Korean Wave than other variables. It will be necessary to have a policy that will lead to a substantial revisit of tourists by enhancing tourist attractions for the purpose of Korean Wave. Lastly, the recommendation had the same result of satisfaction as the sightseeing spot attraction and food satisfaction have higher ${\beta}$ value than other variables. From this analysis, we found that 'food satisfaction' and 'sightseeing spot attraction' variables were the common factors to influence three dependent variables that are mentioned above('Overall satisfaction', 'Revisit intention' and 'Recommendation'), and that those factors affected the satisfaction of travel in Korea significantly. The purpose of this study is to examine how to activate foreign tourists in Korea through big data analysis. It is expected to be used as basic data for analyzing tourism data and establishing effective tourism policy. It is expected to be used as a material to establish an activation plan that can contribute to tourism development in Korea in the future.

• The Korean Society of Law and Medicine
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• v.23 no.4
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• pp.29-74
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• 2022

As social disasters occur under the Disaster Management Act, which can damage the people's "life, body, and property" due to the rapid spread and spread of unexpected COVID-19 infectious diseases in 2020, information collected through inspection and reporting of infectious disease pathogens (Article 11), epidemiological investigation (Article 18), epidemiological investigation for vaccination (Article 29), artificial technology, and prevention policy Decision), (3) It was used as an important basis for decision-making in the context of an infectious disease crisis, such as promoting vaccination and understanding the current status of damage. In addition, medical policy decisions using infectious disease data contribute to quarantine policy decisions, information provision, drug development, and research technology development, and interest in the legal scope and limitations of using infectious disease data has increased worldwide. The use of infectious disease data can be classified for the purpose of spreading and blocking infectious diseases, prevention, management, and treatment of infectious diseases, and the use of information will be more widely made in the context of an infectious disease crisis. In particular, as the serious stage of the Disaster Management Act continues, the processing of personal identification information and sensitive information becomes an important issue. Information on "medical records, vaccination drugs, vaccination, underlying diseases, health rankings, long-term care recognition grades, pregnancy, etc." needs to be interpreted. In the case of "prevention, management, and treatment of infectious diseases", it is difficult to clearly define the concept of medical practicesThe types of actions are judged based on "legislative purposes, academic principles, expertise, and social norms," but the balance of legal interests should be based on the need for data use in quarantine policies and urgent judgment in public health crises. Specifically, the speed and degree of transmission of infectious diseases in a crisis, whether the purpose can be achieved without processing sensitive information, whether it unfairly violates the interests of third parties or information subjects, and the effectiveness of introducing quarantine policies through processing sensitive information can be used as major evaluation factors. On the other hand, the collection, provision, and use of infectious disease data for research purposes will be used through pseudonym processing under the Personal Information Protection Act, consent under the Bioethics Act and deliberation by the Institutional Bioethics Committee, and data provision deliberation committee. Therefore, the use of research purposes is recognized as long as procedural validity is secured as it is reviewed by the pseudonym processing and data review committee, the consent of the information subject, and the institutional bioethics review committee. However, the burden on research managers should be reduced by clarifying the pseudonymization or anonymization procedures, the introduction or consent procedures of the comprehensive consent system and the opt-out system should be clearly prepared, and the procedure for re-identifying or securing security that may arise from technological development should be clearly defined.

• Journal of Preventive Medicine and Public Health
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• v.7 no.1
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• pp.29-94
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• 1974

Today most developed countries provide modern medical care for most of the population. The rural area is the more neglected area in the medical and health field. In public health, the philosophy is that medical care for in maintenance of health is a basic right of man; it should not be discriminated against racial, environmental or financial situations. The deficiency of the medical care system, cultural bias, economic development, and ignorance of the residents about health care brought about the shortage of medical personnel and facilities on the rural areas. Moreover, medical students and physicians have been taught less about rural health care than about urban health care. Medical care, therefore, is insufficient in terms of health care personnel/and facilities in rural areas. Under such a situation, there is growing concern about the health problems among the rural population. The findings presented in this report are useful measures of the major health problems and even more important, as a guide to planning for improved medical care systems. It is hoped that findings from this study will be useful to those responsible for improving the delivery of health service for the rural population. Objectives: -to determine the health status of the residents in the rural areas. -to assess the rural population's needs in terms of health and medical care. -to make recommendations concerning improvement in the delivery of health and medical care for the rural population. Procedures: For the sampling design, the ideal would be to sample according to the proportion of the composition age-groups. As the health problems would be different by group, the sample was divided into 10 different age-groups. If the sample were allocated by proportion of composition of each age group, some age groups would be too small to estimate the health problem. The sample size of each age-group population was 100 people/age-groups. Personal interviews were conducted by specially trained medical students. The interviews dealt at length with current health status, medical care problems, utilization of medical services, medical cost paid for medical care and attitudes toward health. In addition, more information was gained from the public health field, including environmental sanitation, maternal and child health, family planning, tuberculosis control, and dental health. The sample Sample size was one fourth of total population: 1,438 The aged 10-14 years showed the largest number of 254 and the aged under one year was the smallest number of 81. Participation in examination Examination sessions usually were held in the morning every Tuesday, Wenesday, and Thursday for 3 hours at each session at the Namchun Health station. In general, the rate of participation in medical examination was low especially in ages between 10-19 years old. The highest rate of participation among are groups was the under one year age-group by 100 percent. The lowest use rate as low as 3% of those in the age-groups 10-19 years who are attending junior and senior high school in Taegu city so the time was not convenient for them to recieve examinations. Among the over 20 years old group, the rate of participation of female was higher than that of males. The results are as follows: A. Publie health problems Population: The number of pre-school age group who required child health was 724, among them infants numbered 96. Number of eligible women aged 15-44 years was 1,279, and women with husband who need maternal health numbered 700. The age-group of 65 years or older was 201 needed more health care and 65 of them had disabilities. (Table 2). Environmental sanitation: Seventy-nine percent of the residents relied upon well water as a primary source of dringking water. Ninety-three percent of the drinking water supply was rated as unfited quality for drinking. More than 90% of latrines were unhygienic, in structure design and sanitation (Table 15). Maternal and child health: Maternal health Average number of pregnancies of eligible women was 4 times. There was almost no pre- and post-natal care. Pregnancy wastage Still births was 33 per 1,000 live births. Spontaneous abortion was 156 per 1,000 live births. Induced abortion was 137 per 1,000 live births. Delivery condition More than 90 percent of deliveries were conducted at home. Attendants at last delivery were laymen by 76% and delivery without attendants was 14%. The rate of non-sterilized scissors as an instrument used to cut the umbilical cord was as high as 54% and of sickles was 14%. The rate of difficult delivery counted for 3%. Maternal death rate estimates about 35 per 10,000 live births. Child health Consultation rate for child health was almost non existant. In general, vaccination rate of children was low; vaccination rates for children aged 0-5 years with BCG and small pox were 34 and 28 percent respectively. The rate of vaccination with DPT and Polio were 23 and 25% respectively but the rate of the complete three injections were as low as 5 and 3% respectively. The number of dead children was 280 per 1,000 living children. Infants death rate was 45 per 1,000 live births (Table 16), Family planning: Approval rate of married women for family planning was as high as 86%. The rate of experiences of contraception in the past was 51%. The current rate of contraception was 37%. Willingness to use contraception in the future was as high as 86% (Table 17). Tuberculosis control: Number of registration patients at the health center currently was 25. The number indicates one eighth of estimate number of tuberculosis in the area. Number of discharged cases in the past accounted for 79 which showed 50% of active cases when discharged time. Rate of complete treatment among reasons of discharge in the past as low as 28%. There needs to be a follow up observation of the discharged cases (Table 18). Dental problems: More than 50% of the total population have at least one or more dental problems. (Table 19) B. Medical care problems Incidence rate: 1. In one month Incidence rate of medical care problems during one month was 19.6 percent. Among these health problems which required rest at home were 11.8 percent. The estimated number of patients in the total population is 1,206. The health problems reported most frequently in interviews during one month are: GI trouble, respiratory disease, neuralgia, skin disease, and communicable disease-in that order, The rate of health problems by age groups was highest in the 1-4 age group and in the 60 years or over age group, the lowest rate was the 10-14 year age group. In general, 0-29 year age group except the 1-4 year age group was low incidence rate. After 30 years old the rate of health problems increases gradually with aging. Eighty-three percent of health problems that occured during one month were solved by primary medical care procedures. Seventeen percent of health problems needed secondary care. Days rested at home because of illness during one month were 0.7 days per interviewee and 8days per patient and it accounts for 2,161 days for the total productive population in the area. (Table 20) 2. In a year The incidence rate of medical care problems during a year was 74.8%, among them health problems which required rest at home was 37 percent. Estimated number of patients in the total population during a year was 4,600. The health problems that occured most frequently among the interviewees during a year were: Cold (30%), GI trouble (18), respiratory disease (11), anemia (10), diarrhea (10), neuralgia (10), parasite disease (9), ENT (7), skin (7), headache (7), trauma (4), communicable disease (3), and circulatory disease (3) -in that order. The rate of health problems by age groups was highest in the infants group, thereafter the rate decreased gradually until the age 15-19 year age group which showed the lowest, and then the rate increased gradually with aging. Eighty-seven percent of health problems during a year were solved by primary medical care. Thirteen percent of them needed secondary medical care procedures. Days rested at home because of illness during a year were 16 days per interviewee and 44 days per patient and it accounted for 57,335 days lost among productive age group in the area (Table 21). Among those given medical examination, the conditions observed most frequently were respiratory disease, GI trouble, parasite disease, neuralgia, skin disease, trauma, tuberculosis, anemia, chronic obstructive lung disease, eye disorders-in that order (Table 22). The main health problems required secondary medical care are as fellows: (previous page). Utilization of medical care (treatment) The rate of treatment by various medical facilities for all health problems during one month was 73 percent. The rate of receiving of medical care of those who have health problems which required rest at home was 52% while the rate of those who have health problems which did not required rest was 61 percent (Table 23). The rate of receiving of medical care for all health problems during a year was 67 percent. The rate of receiving of medical care of those who have health problems which required rest at home was 82 percent while the rate of those who have health problems which did not required rest was as low as 53 percent (Table 24). Types of medical facilitied used were as follows: Hospital and clinics: 32-35% Herb clinics: 9-10% Drugstore: 53-58% Hospitalization Rate of hospitalization was 1.7% and the estimate number of hospitalizations among the total population during a year will be 107 persons (Table 25). Medical cost: Average medical cost per person during one month and a year were 171 and 2,800 won respectively. Average medical cost per patient during one month and a year were 1,109 and 3,740 won respectively. Average cost per household during a year was 15,800 won (Table 26, 27). Solution measures for health and medical care problems in rural area: A. Health problems which could be solved by paramedical workers such as nurses, midwives and aid nurses etc. are as follows: 1. Improvement of environmental sanitation 2. MCH except medical care problems 3. Family planning except surgical intervention 4. Tuberculosis control except diagnosis and prescription 5. Dental care except operational intervention 6. Health education for residents for improvement of utilization of medical facilities and early diagnosis etc. B. Medical care problems 1. Eighty-five percent of health problems could be solved by primary care procedures by general practitioners. 2. Fifteen percent of health problems need secondary medical procedures by a specialist. C. Medical cost Concidering the economic situation in rural area the amount of 2,062 won per residents during a year will be burdensome, so financial assistance is needed gorvernment to solve health and medical care problems for rural people.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.95-108
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• 2017

Recently, AlphaGo which is Bakuk (Go) artificial intelligence program by Google DeepMind, had a huge victory against Lee Sedol. Many people thought that machines would not be able to win a man in Go games because the number of paths to make a one move is more than the number of atoms in the universe unlike chess, but the result was the opposite to what people predicted. After the match, artificial intelligence technology was focused as a core technology of the fourth industrial revolution and attracted attentions from various application domains. Especially, deep learning technique have been attracted as a core artificial intelligence technology used in the AlphaGo algorithm. The deep learning technique is already being applied to many problems. Especially, it shows good performance in image recognition field. In addition, it shows good performance in high dimensional data area such as voice, image and natural language, which was difficult to get good performance using existing machine learning techniques. However, in contrast, it is difficult to find deep leaning researches on traditional business data and structured data analysis. In this study, we tried to find out whether the deep learning techniques have been studied so far can be used not only for the recognition of high dimensional data but also for the binary classification problem of traditional business data analysis such as customer churn analysis, marketing response prediction, and default prediction. And we compare the performance of the deep learning techniques with that of traditional artificial neural network models. The experimental data in the paper is the telemarketing response data of a bank in Portugal. It has input variables such as age, occupation, loan status, and the number of previous telemarketing and has a binary target variable that records whether the customer intends to open an account or not. In this study, to evaluate the possibility of utilization of deep learning algorithms and techniques in binary classification problem, we compared the performance of various models using CNN, LSTM algorithm and dropout, which are widely used algorithms and techniques in deep learning, with that of MLP models which is a traditional artificial neural network model. However, since all the network design alternatives can not be tested due to the nature of the artificial neural network, the experiment was conducted based on restricted settings on the number of hidden layers, the number of neurons in the hidden layer, the number of output data (filters), and the application conditions of the dropout technique. The F1 Score was used to evaluate the performance of models to show how well the models work to classify the interesting class instead of the overall accuracy. The detail methods for applying each deep learning technique in the experiment is as follows. The CNN algorithm is a method that reads adjacent values from a specific value and recognizes the features, but it does not matter how close the distance of each business data field is because each field is usually independent. In this experiment, we set the filter size of the CNN algorithm as the number of fields to learn the whole characteristics of the data at once, and added a hidden layer to make decision based on the additional features. For the model having two LSTM layers, the input direction of the second layer is put in reversed position with first layer in order to reduce the influence from the position of each field. In the case of the dropout technique, we set the neurons to disappear with a probability of 0.5 for each hidden layer. The experimental results show that the predicted model with the highest F1 score was the CNN model using the dropout technique, and the next best model was the MLP model with two hidden layers using the dropout technique. In this study, we were able to get some findings as the experiment had proceeded. First, models using dropout techniques have a slightly more conservative prediction than those without dropout techniques, and it generally shows better performance in classification. Second, CNN models show better classification performance than MLP models. This is interesting because it has shown good performance in binary classification problems which it rarely have been applied to, as well as in the fields where it's effectiveness has been proven. Third, the LSTM algorithm seems to be unsuitable for binary classification problems because the training time is too long compared to the performance improvement. From these results, we can confirm that some of the deep learning algorithms can be applied to solve business binary classification problems.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.32 no.1
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• pp.93-106
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• 2014

In this study, Analyze environment of location, investigation into vegetation resources, survey management status and establish to classify the management area for Natural monument No.374 Pyengdae-ri Torreya nucifera forest. The results were as follows: First, Torreya nucifera forest is concerned about influence of development caused by utilization of land changes to agricultural region. Thus, establish to preservation management plan for preservation of prototypical and should be excluded development activity to cause the change of terrain that Gotjawal in the Torreya nucifera forest is factor of base for generating species diversity. Secondly, Torreya nucifera forest summarized as 402 taxa composed 91 familly 263 genus, 353 species, 41 varieties and 8 forms. The distribution of plants for the first grade & second grade appear of endangered plant to Ministry of Environment specify. But, critically endangered in forest by changes in habitat, diseases and illegal overcatching. Therefore, when establishing forest management plan should be considered for put priority on protection. Thirdly, Torreya nucifera representing the upper layer of the vegetation structure. But, old tree oriented management and conservation strategy result in poor age structure. Furthermore, desiccation of forest on artificial management and decline in Torreya nucifera habitat on ecological succession can indicate a problem in forest. Therefore, establish plan such as regulation of population density and sapling tree proliferation for sustainable characteristics of the Torreya nucifera forest. Fourth, Appear to damaged of trails caused by use. Especially, Scoria way occurs a lot of damaged and higher than the share ratio of each section. Therefore, share ratio reduction Plan should be considered through the additional development of tourism routes rather than the replacement of Scoria. Fifth, Representing high preference of the Torreya nucifera forest tourist factor confirmed the plant elements. It is sensitive to usage pressure. And requires continuous monitoring by characteristic of Non-permanent. In addition, need an additional plan such as additional development of tourism elements and active utilizing an element of high preference. Sixth, Strength of protected should be differently accordance with importance. First grade area have to maintenance of plant population and natural habitats. Set the direction of the management. Second grade areas focus on annual regeneration of the forest. Third grade area should be utilized demonstration forest or set to the area for proliferate sapling. Fourth grade areas require the introduced of partial rest system that disturbance are often found in proper vegetation. Fifth grade area appropriate to the service area for promoting tourism by utilizing natural resources in Torreya nucifera forest. Furthermore, installation of a buffer zone in relatively low ratings area and periodic monitoring to the improvement of edge effect that adjacent areas of different class.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.221-241
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• 2018

Deep learning is getting attention recently. The deep learning technique which had been applied in competitions of the International Conference on Image Recognition Technology(ILSVR) and AlphaGo is Convolution Neural Network(CNN). CNN is characterized in that the input image is divided into small sections to recognize the partial features and combine them to recognize as a whole. Deep learning technologies are expected to bring a lot of changes in our lives, but until now, its applications have been limited to image recognition and natural language processing. The use of deep learning techniques for business problems is still an early research stage. If their performance is proved, they can be applied to traditional business problems such as future marketing response prediction, fraud transaction detection, bankruptcy prediction, and so on. So, it is a very meaningful experiment to diagnose the possibility of solving business problems using deep learning technologies based on the case of online shopping companies which have big data, are relatively easy to identify customer behavior and has high utilization values. Especially, in online shopping companies, the competition environment is rapidly changing and becoming more intense. Therefore, analysis of customer behavior for maximizing profit is becoming more and more important for online shopping companies. In this study, we propose 'CNN model of Heterogeneous Information Integration' using CNN as a way to improve the predictive power of customer behavior in online shopping enterprises. In order to propose a model that optimizes the performance, which is a model that learns from the convolution neural network of the multi-layer perceptron structure by combining structured and unstructured information, this model uses 'heterogeneous information integration', 'unstructured information vector conversion', 'multi-layer perceptron design', and evaluate the performance of each architecture, and confirm the proposed model based on the results. In addition, the target variables for predicting customer behavior are defined as six binary classification problems: re-purchaser, churn, frequent shopper, frequent refund shopper, high amount shopper, high discount shopper. In order to verify the usefulness of the proposed model, we conducted experiments using actual data of domestic specific online shopping company. This experiment uses actual transactions, customers, and VOC data of specific online shopping company in Korea. Data extraction criteria are defined for 47,947 customers who registered at least one VOC in January 2011 (1 month). The customer profiles of these customers, as well as a total of 19 months of trading data from September 2010 to March 2012, and VOCs posted for a month are used. The experiment of this study is divided into two stages. In the first step, we evaluate three architectures that affect the performance of the proposed model and select optimal parameters. We evaluate the performance with the proposed model. Experimental results show that the proposed model, which combines both structured and unstructured information, is superior compared to NBC(Naïve Bayes classification), SVM(Support vector machine), and ANN(Artificial neural network). Therefore, it is significant that the use of unstructured information contributes to predict customer behavior, and that CNN can be applied to solve business problems as well as image recognition and natural language processing problems. It can be confirmed through experiments that CNN is more effective in understanding and interpreting the meaning of context in text VOC data. And it is significant that the empirical research based on the actual data of the e-commerce company can extract very meaningful information from the VOC data written in the text format directly by the customer in the prediction of the customer behavior. Finally, through various experiments, it is possible to say that the proposed model provides useful information for the future research related to the parameter selection and its performance.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.34 no.s02
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• pp.45-65
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• 1989

The Korean peninsular having the complexity of the photography and variability of climate is located within passing area of a lots of typhoon occurring from the southern islands of Philippines. So, there are various patterns of wind and flooding damages in paddy field occuring by the strong wind and the heavy rain concentrated during the summer season of rice growing period in Korea. The wind damages to rice plants in Korea were mainly caused by saline wind, dry wind and strong wind when typhoon occurred. The saline wind damage having symptom of white head or dried leaves occurred by 1.1 to 17.2 mg of salt per dry weight stuck on the plant which was located at 2. 5km away from seashore of southern coastal area during the period(from 27th to 29th, August, 1986) of typhoon &Vera& accompanying 62-96％ of relative humidity, more than 6 m per second of wind velocity and 22.5 to 26.4$^{\circ}C$ of air temperature without rain. Most of the typhoons accompanying 4.0 to 8. 5m per second of wind and low humidity (lesp an 60％) with high temperature in the east coastal area and southen area of Korea. were changed to dry and hot wind by the foehn phenomenon. The dry wind damages with the symptom of the white head or the discolored brownish grain occurred at the rice heading stage. The strong wind caused the severe damages such as the broken leaves, cut-leaves and dried leaves before heading stage, lodging and shattering of grain at ripening stage mechanically during typhoon. To reduce the wind damages to rice plant, cultivation of resistant varieties to wind damages such as Sangpoongbyeo and Cheongcheongbyeo and the escape of heading stage during period of typhoon by accelerating of heading within 15th, August are effective. Though the flood disasters to rice plant such as earring away of field, burying of field, submerging and lodging damage are getting low by the construction of dam for multiple purpose and river bank, they are occasionally occurred by the regional heavy rain and water filled out in bank around the river. Paddy field were submerged for 2 to 4 days when typhoon and heavy rain occurred about the end of August. At this time, the rice plants that was in younger growing stage in the late transplanting field of southern area of Korea had the severe damages. Although panicles of rice plant which was in the meiotic growing stage and heading stage were died when flooded, they had 66％ of yield compensating ability by the upper tilling panicle produced from tiller with dead panicle in ordinary transplanting paddy field. It is effective for reduction of flooding damages to cultivate the resistant variety to flooding having the resistance to bacterial leaf blight, lodging and small brown planthopper simultaneously. Especially, Tongil type rice varieties are relatively resistant to flooding, compared to Japonica rice varieties. Tongil type rice varieties had high survivals, low elongation ability of leaf sheath and blade, high recovering ability by the high root activity and photosynthesis and high yield compensating ability by the upper tillering panicle when flooded. To minimize the flooding and wind damage to rice plants in future, following research have to be carried out; 1. Data analysis by telemetering and computerization of climate, actual conditions and growing diagnosis of crops damaged by disasters. 2. Development of tolerant varieties to poor natural conditions related to flooding and wind damages. 3. Improvement of the reasonable cropping system by introduction of other crops compensating the loss of the damaged rice. 4. Increament of utilization of rice plant which was damaged.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.1-27
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• 2017

It is known that the economic sentiment index and macroeconomic indicators are closely related because economic agent's judgment and forecast of the business conditions affect economic fluctuations. For this reason, consumer sentiment or confidence provides steady fodder for business and is treated as an important piece of economic information. In Korea, private consumption accounts and consumer sentiment index highly relevant for both, which is a very important economic indicator for evaluating and forecasting the domestic economic situation. However, despite offering relevant insights into private consumption and GDP, the traditional approach to measuring the consumer confidence based on the survey has several limits. One possible weakness is that it takes considerable time to research, collect, and aggregate the data. If certain urgent issues arise, timely information will not be announced until the end of each month. In addition, the survey only contains information derived from questionnaire items, which means it can be difficult to catch up to the direct effects of newly arising issues. The survey also faces potential declines in response rates and erroneous responses. Therefore, it is necessary to find a way to complement it. For this purpose, we construct and assess an index designed to measure consumer economic sentiment index using sentiment analysis. Unlike the survey-based measures, our index relies on textual analysis to extract sentiment from economic and financial news articles. In particular, text data such as news articles and SNS are timely and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. There exist two main approaches to the automatic extraction of sentiment from a text, we apply the lexicon-based approach, using sentiment lexicon dictionaries of words annotated with the semantic orientations. In creating the sentiment lexicon dictionaries, we enter the semantic orientation of individual words manually, though we do not attempt a full linguistic analysis (one that involves analysis of word senses or argument structure); this is the limitation of our research and further work in that direction remains possible. In this study, we generate a time series index of economic sentiment in the news. The construction of the index consists of three broad steps: (1) Collecting a large corpus of economic news articles on the web, (2) Applying lexicon-based methods for sentiment analysis of each article to score the article in terms of sentiment orientation (positive, negative and neutral), and (3) Constructing an economic sentiment index of consumers by aggregating monthly time series for each sentiment word. In line with existing scholarly assessments of the relationship between the consumer confidence index and macroeconomic indicators, any new index should be assessed for its usefulness. We examine the new index's usefulness by comparing other economic indicators to the CSI. To check the usefulness of the newly index based on sentiment analysis, trend and cross - correlation analysis are carried out to analyze the relations and lagged structure. Finally, we analyze the forecasting power using the one step ahead of out of sample prediction. As a result, the news sentiment index correlates strongly with related contemporaneous key indicators in almost all experiments. We also find that news sentiment shocks predict future economic activity in most cases. In almost all experiments, the news sentiment index strongly correlates with related contemporaneous key indicators. Furthermore, in most cases, news sentiment shocks predict future economic activity; in head-to-head comparisons, the news sentiment measures outperform survey-based sentiment index as CSI. Policy makers want to understand consumer or public opinions about existing or proposed policies. Such opinions enable relevant government decision-makers to respond quickly to monitor various web media, SNS, or news articles. Textual data, such as news articles and social networks (Twitter, Facebook and blogs) are generated at high-speeds and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. Although research using unstructured data in economic analysis is in its early stages, but the utilization of data is expected to greatly increase once its usefulness is confirmed.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.71-90
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• 2020

Recently, the global insurance industry is rapidly developing digital transformation through the use of artificial intelligence technologies such as machine learning, natural language processing, and deep learning. As a result, more and more foreign insurers have achieved the success of artificial intelligence technology-based InsurTech and platform business, and Ping An Insurance Group Ltd., China's largest private company, is leading China's global fourth industrial revolution with remarkable achievements in InsurTech and Digital Platform as a result of its constant innovation, using 'finance and technology' and 'finance and ecosystem' as keywords for companies. In response, this study analyzed the InsurTech and platform business activities of Ping An Insurance Group Ltd. through the ser-M analysis model to provide strategic implications for revitalizing AI technology-based businesses of domestic insurers. The ser-M analysis model has been studied so that the vision and leadership of the CEO, the historical environment of the enterprise, the utilization of various resources, and the unique mechanism relationships can be interpreted in an integrated manner as a frame that can be interpreted in terms of the subject, environment, resource and mechanism. As a result of the case analysis, Ping An Insurance Group Ltd. has achieved cost reduction and customer service development by digitally innovating its entire business area such as sales, underwriting, claims, and loan service by utilizing core artificial intelligence technologies such as facial, voice, and facial expression recognition. In addition, "online data in China" and "the vast offline data and insights accumulated by the company" were combined with new technologies such as artificial intelligence and big data analysis to build a digital platform that integrates financial services and digital service businesses. Ping An Insurance Group Ltd. challenged constant innovation, and as of 2019, sales reached $155 billion, ranking seventh among all companies in the Global 2000 rankings selected by Forbes Magazine. Analyzing the background of the success of Ping An Insurance Group Ltd. from the perspective of ser-M, founder Mammingz quickly captured the development of digital technology, market competition and changes in population structure in the era of the fourth industrial revolution, and established a new vision and displayed an agile leadership of digital technology-focused. Based on the strong leadership led by the founder in response to environmental changes, the company has successfully led InsurTech and Platform Business through innovation of internal resources such as investment in artificial intelligence technology, securing excellent professionals, and strengthening big data capabilities, combining external absorption capabilities, and strategic alliances among various industries. Through this success story analysis of Ping An Insurance Group Ltd., the following implications can be given to domestic insurance companies that are preparing for digital transformation. First, CEOs of domestic companies also need to recognize the paradigm shift in industry due to the change in digital technology and quickly arm themselves with digital technology-oriented leadership to spearhead the digital transformation of enterprises. Second, the Korean government should urgently overhaul related laws and systems to further promote the use of data between different industries and provide drastic support such as deregulation, tax benefits and platform provision to help the domestic insurance industry secure global competitiveness. Third, Korean companies also need to make bolder investments in the development of artificial intelligence technology so that systematic securing of internal and external data, training of technical personnel, and patent applications can be expanded, and digital platforms should be quickly established so that diverse customer experiences can be integrated through learned artificial intelligence technology. Finally, since there may be limitations to generalization through a single case of an overseas insurance company, I hope that in the future, more extensive research will be conducted on various management strategies related to artificial intelligence technology by analyzing cases of multiple industries or multiple companies or conducting empirical research.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.57-79
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• 2016

It is a rising trend that the number of users using one of the social media channels, the Social Network Service, so called the SNS, is getting increased. As per to this social trend, more companies have interest in this networking platform and start to invest their funds in it. It has received much attention as a tool spreading and expanding the message that a company wants to deliver to its customers and has been recognized as an important channel in terms of the relationship marketing with them. The environment of media that is radically changing these days makes possible for companies to approach their customers in various ways. Particularly, the social network service, which has been developed rapidly, provides the environment that customers can freely talk about products. For companies, it also works as a channel that gives customized information to customers. To succeed in the online environment, companies need to not only build the relationship between companies and customers but focus on the relationship between customers as well. In response to the online environment with the continuous development of technology, companies have tirelessly made the novel marketing strategy. Especially, as the one-to-one marketing to customers become available, it is more important for companies to maintain the relationship marketing with their customers. Among many SNS, Facebook, which many companies use as a communication channel, provides a fan page service for each company that supports its business. Facebook fan page is the platform that the event, information and announcement can be shared with customers using texts, videos, and pictures. Companies open their own fan pages in order to inform their companies and businesses. Such page functions as the websites of companies and has a characteristic of their brand communities such as blogs as well. As Facebook has become the major communication medium with customers, companies recognize its importance as the effective marketing channel, but they still need to investigate their business performances by using Facebook. Although there are infinite potentials in Facebook fan page that even has a function as a community between users, which other platforms do not, it is incomplete to regard companies' Facebook fan pages as communities and analyze them. In this study, it explores the relationship among customers through the network of the Facebook fan page users. The previous studies on a company's Facebook fan page were focused on finding out the effective operational direction by analyzing the use state of the company. However, in this study, it draws out the structural variable of the network, which customer committment can be measured by applying the social network analysis methodology and investigates the influence of the structural characteristics of network on the business performance of companies in an empirical way. Through each company's Facebook fan page, the network of users who engaged in the communication with each company is exploited and it is the one-mode undirected binary network that respectively regards users and the relationship of them in terms of their marketing activities as the node and link. In this network, it draws out the structural variable of network that can explain the customer commitment, who pressed "like," made comments and shared the Facebook marketing message, of each company by calculating density, global clustering coefficient, mean geodesic distance, diameter. By exploiting companies' historical performance such as net income and Tobin's Q indicator as the result variables, this study investigates influence on companies' business performances. For this purpose, it collects the network data on the subjects of 54 companies among KOSPI-listed companies, which have posted more than 100 articles on their Facebook fan pages during the data collection period. Then it draws out the network indicator of each company. The indicator related to companies' performances is calculated, based on the posted value on DART website of the Financial Supervisory Service. From the academic perspective, this study suggests a new approach through the social network analysis methodology to researchers who attempt to study the business-purpose utilization of the social media channel. From the practical perspective, this study proposes the more substantive marketing performance measurements to companies performing marketing activities through the social media and it is expected that it will bring a foundation of establishing smart business strategies by using the network indicators.