• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.113-125
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• 2013

Every company wants to know customer's requirement and makes an effort to meet them. Cause that, communication between customer and company became core competition of business and that important is increasing continuously. There are several strategies to find customer's needs, but VOC (Voice of customer) is one of most powerful communication tools and VOC gathering by several channels as telephone, post, e-mail, website and so on is so meaningful. So, almost company is gathering VOC and operating VOC system. VOC is important not only to business organization but also public organization such as government, education institute, and medical center that should drive up public service quality and customer satisfaction. Accordingly, they make a VOC gathering and analyzing System and then use for making a new product and service, and upgrade. In recent years, innovations in internet and ICT have made diverse channels such as SNS, mobile, website and call-center to collect VOC data. Although a lot of VOC data is collected through diverse channel, the proper utilization is still difficult. It is because the VOC data is made of very emotional contents by voice or text of informal style and the volume of the VOC data are so big. These unstructured big data make a difficult to store and analyze for use by human. So that, the organization need to automatic collecting, storing, classifying and analyzing system for unstructured big VOC data. This study propose an intelligent VOC analyzing system based on opinion mining to classify the unstructured VOC data automatically and determine the polarity as well as the type of VOC. And then, the basis of the VOC opinion analyzing system, called domain-oriented sentiment dictionary is created and corresponding stages are presented in detail. The experiment is conducted with 4,300 VOC data collected from a medical website to measure the effectiveness of the proposed system and utilized them to develop the sensitive data dictionary by determining the special sentiment vocabulary and their polarity value in a medical domain. Through the experiment, it comes out that positive terms such as "칭찬, 친절함, 감사, 무사히, 잘해, 감동, 미소" have high positive opinion value, and negative terms such as "퉁명, 뭡니까, 말하더군요, 무시하는" have strong negative opinion. These terms are in general use and the experiment result seems to be a high probability of opinion polarity. Furthermore, the accuracy of proposed VOC classification model has been compared and the highest classification accuracy of 77.8% is conformed at threshold with -0.50 of opinion classification of VOC. Through the proposed intelligent VOC analyzing system, the real time opinion classification and response priority of VOC can be predicted. Ultimately the positive effectiveness is expected to catch the customer complains at early stage and deal with it quickly with the lower number of staff to operate the VOC system. It can be made available human resource and time of customer service part. Above all, this study is new try to automatic analyzing the unstructured VOC data using opinion mining, and shows that the system could be used as variable to classify the positive or negative polarity of VOC opinion. It is expected to suggest practical framework of the VOC analysis to diverse use and the model can be used as real VOC analyzing system if it is implemented as system. Despite experiment results and expectation, this study has several limits. First of all, the sample data is only collected from a hospital web-site. It means that the sentimental dictionary made by sample data can be lean too much towards on that hospital and web-site. Therefore, next research has to take several channels such as call-center and SNS, and other domain like government, financial company, and education institute.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.173-198
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• 2020

For a long time, many studies have been conducted on predicting the success of campaigns for customers in academia, and prediction models applying various techniques are still being studied. Recently, as campaign channels have been expanded in various ways due to the rapid revitalization of online, various types of campaigns are being carried out by companies at a level that cannot be compared to the past. However, customers tend to perceive it as spam as the fatigue of campaigns due to duplicate exposure increases. Also, from a corporate standpoint, there is a problem that the effectiveness of the campaign itself is decreasing, such as increasing the cost of investing in the campaign, which leads to the low actual campaign success rate. Accordingly, various studies are ongoing to improve the effectiveness of the campaign in practice. This campaign system has the ultimate purpose to increase the success rate of various campaigns by collecting and analyzing various data related to customers and using them for campaigns. In particular, recent attempts to make various predictions related to the response of campaigns using machine learning have been made. It is very important to select appropriate features due to the various features of campaign data. If all of the input data are used in the process of classifying a large amount of data, it takes a lot of learning time as the classification class expands, so the minimum input data set must be extracted and used from the entire data. In addition, when a trained model is generated by using too many features, prediction accuracy may be degraded due to overfitting or correlation between features. Therefore, in order to improve accuracy, a feature selection technique that removes features close to noise should be applied, and feature selection is a necessary process in order to analyze a high-dimensional data set. Among the greedy algorithms, SFS (Sequential Forward Selection), SBS (Sequential Backward Selection), SFFS (Sequential Floating Forward Selection), etc. are widely used as traditional feature selection techniques. It is also true that if there are many risks and many features, there is a limitation in that the performance for classification prediction is poor and it takes a lot of learning time. Therefore, in this study, we propose an improved feature selection algorithm to enhance the effectiveness of the existing campaign. The purpose of this study is to improve the existing SFFS sequential method in the process of searching for feature subsets that are the basis for improving machine learning model performance using statistical characteristics of the data to be processed in the campaign system. Through this, features that have a lot of influence on performance are first derived, features that have a negative effect are removed, and then the sequential method is applied to increase the efficiency for search performance and to apply an improved algorithm to enable generalized prediction. Through this, it was confirmed that the proposed model showed better search and prediction performance than the traditional greed algorithm. Compared with the original data set, greed algorithm, genetic algorithm (GA), and recursive feature elimination (RFE), the campaign success prediction was higher. In addition, when performing campaign success prediction, the improved feature selection algorithm was found to be helpful in analyzing and interpreting the prediction results by providing the importance of the derived features. This is important features such as age, customer rating, and sales, which were previously known statistically. Unlike the previous campaign planners, features such as the combined product name, average 3-month data consumption rate, and the last 3-month wireless data usage were unexpectedly selected as important features for the campaign response, which they rarely used to select campaign targets. It was confirmed that base attributes can also be very important features depending on the type of campaign. Through this, it is possible to analyze and understand the important characteristics of each campaign type.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.175-196
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• 2022

Information and communication and home appliance industries, which were one of South Korea's main industries, are gradually losing their export share as their export competitiveness is weakening. This study objectively analyzed export competitiveness and suggested export-promising countries in order to help South Korea's information communication and home appliance industries improve exports. In this study, network properties, centrality, and structural hole analysis were performed during network analysis to evaluate export competitiveness. In order to select promising export countries, we proposed a new variable that can take into account the characteristics of an already established International Trade Network (ITN), that is, the Global Value Chain (GVC), in addition to the existing economic factors. The conditional log-odds for individual links derived from the Exponential Random Graph Model (ERGM) in the analysis of the cross-border trade network were assumed as a proxy variable that can indicate the export potential. In consideration of the possibility of ERGM linkage, a parametric approach and a non-parametric approach were used to recommend export-promising countries, respectively. In the parametric method, a regression analysis model was developed to predict the export value of the information and communication and home appliance industries in South Korea by additionally considering the link-specific characteristics of the network derived from the ERGM to the existing economic factors. Also, in the non-parametric approach, an abnormality detection algorithm based on the clustering method was used, and a promising export country was proposed as a method of finding outliers that deviate from two peers. According to the research results, the structural characteristic of the export network of the industry was a network with high transferability. Also, according to the centrality analysis result, South Korea's influence on exports was weak compared to its size, and the structural hole analysis result showed that export efficiency was weak. According to the model for recommending promising exporting countries proposed by this study, in parametric analysis, Iran, Ireland, North Macedonia, Angola, and Pakistan were promising exporting countries, and in nonparametric analysis, Qatar, Luxembourg, Ireland, North Macedonia and Pakistan were analyzed as promising exporting countries. There were differences in some countries in the two models. The results of this study revealed that the export competitiveness of South Korea's information and communication and home appliance industries in GVC was not high compared to the size of exports, and thus showed that exports could be further reduced. In addition, this study is meaningful in that it proposed a method to find promising export countries by considering GVC networks with other countries as a way to increase export competitiveness. This study showed that, from a policy point of view, the international trade network of the information communication and home appliance industries has an important mutual relationship, and although transferability is high, it may not be easily expanded to a three-party relationship. In addition, it was confirmed that South Korea's export competitiveness or status was lower than the export size ranking. This paper suggested that in order to improve the low out-degree centrality, it is necessary to increase exports to Italy or Poland, which had significantly higher in-degrees. In addition, we argued that in order to improve the centrality of out-closeness, it is necessary to increase exports to countries with particularly high in-closeness. In particular, it was analyzed that Morocco, UAE, Argentina, Russia, and Canada should pay attention as export countries. This study also provided practical implications for companies expecting to expand exports. The results of this study argue that companies expecting export expansion need to pay attention to countries with a relatively high potential for export expansion compared to the existing export volume by country. In particular, for companies that export daily necessities, countries that should pay attention to the population are presented, and for companies that export high-end or durable products, countries with high GDP, or purchasing power, relatively low exports are presented. Since the process and results of this study can be easily extended and applied to other industries, it is also expected to develop services that utilize the results of this study in the public sector.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.1-33
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• 2019

The small and medium sized enterprises (hereinafter SMEs) are already at a competitive disadvantaged when compared to large companies with more abundant resources. Manufacturing SMEs not only need a lot of information needed for new product development for sustainable growth and survival, but also seek networking to overcome the limitations of resources, but they are faced with limitations due to their size limitations. In a new era in which connectivity increases the complexity and uncertainty of the business environment, SMEs are increasingly urged to find information and solve networking problems. In order to solve these problems, the government funded research institutes plays an important role and duty to solve the information asymmetry problem of SMEs. The purpose of this study is to identify the differentiating characteristics of SMEs that utilize the public information support infrastructure provided by SMEs to enhance the innovation capacity of SMEs, and how they contribute to corporate performance. We argue that we need an infrastructure for providing information support to SMEs as part of this effort to strengthen of the role of government funded institutions; in this study, we specifically identify the target of such a policy and furthermore empirically demonstrate the effects of such policy-based efforts. Our goal is to help establish the strategies for building the information supporting infrastructure. To achieve this purpose, we first classified the characteristics of SMEs that have been found to utilize the information supporting infrastructure provided by government funded institutions. This allows us to verify whether selection bias appears in the analyzed group, which helps us clarify the interpretative limits of our study results. Next, we performed mediator and moderator effect analysis for multiple variables to analyze the process through which the use of information supporting infrastructure led to an improvement in external networking capabilities and resulted in enhancing product competitiveness. This analysis helps identify the key factors we should focus on when offering indirect support to SMEs through the information supporting infrastructure, which in turn helps us more efficiently manage research related to SME supporting policies implemented by government funded institutions. The results of this study showed the following. First, SMEs that used the information supporting infrastructure were found to have a significant difference in size in comparison to domestic R&D SMEs, but on the other hand, there was no significant difference in the cluster analysis that considered various variables. Based on these findings, we confirmed that SMEs that use the information supporting infrastructure are superior in size, and had a relatively higher distribution of companies that transact to a greater degree with large companies, when compared to the SMEs composing the general group of SMEs. Also, we found that companies that already receive support from the information infrastructure have a high concentration of companies that need collaboration with government funded institution. Secondly, among the SMEs that use the information supporting infrastructure, we found that increasing external networking capabilities contributed to enhancing product competitiveness, and while this was no the effect of direct assistance, we also found that indirect contributions were made by increasing the open marketing capabilities: in other words, this was the result of an indirect-only mediator effect. Also, the number of times the company received additional support in this process through mentoring related to information utilization was found to have a mediated moderator effect on improving external networking capabilities and in turn strengthening product competitiveness. The results of this study provide several insights that will help establish policies. KISTI's information support infrastructure may lead to the conclusion that marketing is already well underway, but it intentionally supports groups that enable to achieve good performance. As a result, the government should provide clear priorities whether to support the companies in the underdevelopment or to aid better performance. Through our research, we have identified how public information infrastructure contributes to product competitiveness. Here, we can draw some policy implications. First, the public information support infrastructure should have the capability to enhance the ability to interact with or to find the expert that provides required information. Second, if the utilization of public information support (online) infrastructure is effective, it is not necessary to continuously provide informational mentoring, which is a parallel offline support. Rather, offline support such as mentoring should be used as an appropriate device for abnormal symptom monitoring. Third, it is required that SMEs should improve their ability to utilize, because the effect of enhancing networking capacity through public information support infrastructure and enhancing product competitiveness through such infrastructure appears in most types of companies rather than in specific SMEs.

• Journal of dental hygiene science
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• v.16 no.6
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• pp.488-494
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• 2016

The purpose of the present study was to examine dental hygienists' perception of the current national practical examination. This research was performed using 199 self-reported surveys answered by professors of dental hygiene studies and clinical dental hygienist. Frequency analysis, chi-square tests, and analysis of variance were performed by using IBM SPSS Statistics ver. 20.0. The results revealed that many of the respondents consider the current national practical examination to be neutral. They did not think that the current national practical examination questions are useful for assessing occupation-centric integrated clinical practice ability and counseling techniques for patient intervention. The professors of dental hygiene studies believed that among the research tasks required as mentioned in the national practical examination questions, dental polishing and tooth brushing education are of paramount importance, whereas clinical dental hygienists believed that ultrasonic scaling is the most important (p<0.05). Most of the professors of dental hygiene studies reported that they conducted skills education for dental polishing and tooth brushing education, while most of the clinical dental hygienists reported that tasks actually performed in the clinic included impression taking, model fabrication, ultrasonic scaling, and explaining treatment precautions (p<0.05). Therefore, these tasks can be effectively carried out with the improvement of the national dental hygienist practical examination.

• Journal of Life Science
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• v.28 no.7
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• pp.795-801
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• 2018

This study was conducted to investigate the association of single nucleotide polymorphism (SNP) markers on equine chromosomes (ECA) 3 and 9 with body weight in Jeju horses. We used DNA samples and body weight data of 320 horses provided by the Livestock Promotion Agency, Jeju Special Self-Governing Province, and the Korean Racing Association, respectively. We genotyped all the experimental animals using nine SNP markers located on ECA 3 (BIEC2-808466, BIEC2-808543, BIEC2-808967, and BIEC2-809370) and ECA 9 (BIEC2-1105370, BIEC2-1105372, BIEC2-1105377, BIEC21105505, and BIEC2-1105840). These markers were selected due to their effects on body conformation traits in horses. The joint effect of the genotypes of the two SNP markers (BIEC2-808467 and BIEC2-1105377) regarding body weight were also evaluated. The estimated breeding value (EBV) of body weight was obtained as the dependent variable for association analyses using a linear mixed model. Significant associations were detected between SNP markers (BIEC2-808543, BIEC2-808967, BIEC2-809370, BIEC2-1105370, BIEC2-1105372, and BIEC2-1105377) and the body weight EBV. In addition, the joint genotype effect of the BIEC2-808467 and BIEC2-1105377 on the body weight EBV was significant. These results indicate that the SNP markers, which showed their significant effects on body conformation, can be used as genetic markers to improve the efficiency of the selective breeding program for the body weight traits in Jeju horses.

• Journal of Korea Port Economic Association
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• v.24 no.4
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• pp.363-384
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• 2008

This study aims at improving Korea's competitiveness in port logistics through marketing strategy with integrating the conceptual approach into the empirical one and combining both the oldest military treatise and the newest evaluating model in social science that was applied by the HFP(hierarchical fuzzy process) model enhanced by the KJ method. The empirical results of this study show Busan in the middle among subject ports. At present, Korea plays a reciprocal role in the port market in East Asia, but in the medium- and long-term, Korea's ports will vie together with most major ports in the East Asian region. A descriptive investigation shows that Korea's developing tasks in port logistics must be considered in the context of the direction for developing port policies, the necessity of expanding port facilities in the capital region, securing the sufficient traffic volume through the establishment of the hinterland linking system and its positive utilization, and reforming the direction for developing the global logistics through increased port competitiveness. In the short- and medium-term, Korea must use the opportunity factor of 'Growth and open door policy of China' as a geoeconomic advantage and to utilize Korea's ports as a gate to Chinese foreign trade. With the rise of China's economy, China also plays a significant role in both port and airport markets. Hence, the linking system between the two must be established to meet the expanding traffic volume, especially in the capital area. Moreover, it is necessary for Korea to secure port logistics through the establishment of the hinterland linking system and its positive utilization. The great accomplishment of this paper is to present strategies to increase Korea's port competitiveness in the rapidly changing environments of world logistics with the focus on both the oldest military strategic treatise and the newest empirical method in social science. In order to reinforce this study, it needs further compensative research because the evaluation structure could be subdivided with more extensive and precise criteria.

• Journal of Gifted/Talented Education
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• v.22 no.1
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• pp.1-21
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• 2012

The objective of this study is to suggest improvement plan for invention gifted education based on the awareness of teachers and professionals who related to the invention gifted education for the expansion and development of invention gifted education through improvement of relevant problems. To this end, invention gifted education system and its operational status were analyzed, and questionnaire survey on the awareness of the development plan and satisfaction level was conducted, targeting professionals related to the invention gifted education and teachers in charge of invention gifted education classes or gifted education center. The research results are as follows. First, the level of satisfaction on the invention gifted education was greater than normal (M=3.0) in general, but in the field of 'educational materials', 'teacher training programs' and 'human and material support system of support agencies', the level of satisfaction was relatively low, which requires expansion of the support. Second, it is necessary for Korean Intellectual Property Office and Korea Invention Promotion Association to designate and establish specialized research institution to play a key role in enhancing development and efficiency of invention gifted education. As a result of the questionnaire survey, it turned out that expectation and necessity of the specialized research agency was highly recognized. In particular, demand for 'research and development of gifted education method and materials' and 'research and development of teacher training materials and implementation of teacher training' was high among the key areas of the specialized research institution. Third, teachers and professionals related to the invention gifted education responded that 'invention knowledge' in the areas of invention knowledge and thinking and 'entrepreneurship' in the area of invention attitude was somewhat low toward the question on the level of the 9 characteristics of gifted students with invention talents which current beneficiaries of invention gifted education have, which leads to conclusion that review on the model for the selection of gifted children with invention talents as well as research and development of invention gifted education program to enhance characteristics with low levels is required. If long-term development plans and initiatives are deduced based on this, an effective framework for the invention gifted education will be established in the near future. In addition, it is expected that the differentiated political visions and goals will be established in connection with master plan for the promotion of gifted education.

• The Korean Journal of Nuclear Medicine
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• v.37 no.5
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• pp.288-300
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• 2003

Purpose: To obtain regional blood flow and tissue-blood partition coefficient with time-activity curves from ${H_2}^{15}O$ PET, fitting of some parameters in the Kety model is conventionally accomplished by nonlinear least squares (NLS) analysis. However, NLS requires considerable compuation time then is impractical for pixel-by-pixel analysis to generate parametric images of these parameters. In this study, we investigated several fast parameter estimation methods for the parametric image generation and compared their statistical reliability and computational efficiency. Materials and Methods: These methods included linear least squres (LLS), linear weighted least squares (LWLS), linear generalized least squares (GLS), linear generalized weighted least squares (GWLS), weighted Integration (WI), and model-based clustering method (CAKS). ${H_2}^{15}O$ dynamic brain PET with Poisson noise component was simulated using numerical Zubal brain phantom. Error and bias in the estimation of rCBF and partition coefficient, and computation time in various noise environments was estimated and compared. In audition, parametric images from ${H_2}^{15}O$ dynamic brain PET data peformed on 16 healthy volunteers under various physiological conditions was compared to examine the utility of these methods for real human data. Results: These fast algorithms produced parametric images with similar image qualify and statistical reliability. When CAKS and LLS methods were used combinedly, computation time was significantly reduced and less than 30 seconds for $128{\times}128{\times}46$ images on Pentium III processor. Conclusion: Parametric images of rCBF and partition coefficient with good statistical properties can be generated with short computation time which is acceptable in clinical situation.

• Korean Journal of Environmental Agriculture
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• v.18 no.1
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• pp.77-82
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• 1999

Three floating islands have been constructed for water quality improvement for a polluted irrigation reservoir. Each floating island consists of 10 segments. Each segment hay an area of $16m^2$(4×4m) and is made of wood frames and floats(polystyrene foam). We planted three species of aquatic macrophytes(Typha angustifolia, Zizania latifolia, and Phragmites australis) in floating island on June, 1998. They grew very well without death. We would like to evaluate Phragmites australis is the most suitable aquatic macrophyte that could be planted in a floating island because it maintained the best balance of its root and shoot among them. During their grown period, net primary productivity of Typha angustifolia was $962gDM/m^2$, Zizania latifolia was $1,115gDM/m^2$, and Phragmites australis was $523gDM/m^2$. From these data, it would be estimated to 5.0Kg uptake of nitrogen by aquatic macrophytes and phosphorus 0.8Kg in 3 floating islands. The floating islands worked well as a habitat of fish and prawns. Many kinds of insect lived on the floating islands. The floating island has not only the function of water quality treatment but also several advantages: improvement of landscape and species diversity; low cost of maintenance; low technology; unnecessary of energy; less susceptible to variations in pollutant loading. It could be evaluated a good measure of water quality improvement for an irrigation reservoir. However, it should be intensively studied to develop more light, strong, durable and low-priced frames for efficient floating islands.