• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.129-149
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• 2021

Recently, interest in social robots that can socially interact with humans is increasing. Thanks to the development of ICT technology, social robots have become easier to provide personalized services and emotional connection to individuals, and the role of social robots is drawing attention as a means to solve modern social problems and the resulting decline in the quality of individual lives. Along with the interest in social robots, the spread of social robots is also increasing significantly. Many companies are introducing robot products to the market to target various target markets, but so far there is no clear trend leading the market. Accordingly, there are more and more attempts to differentiate robots through the design of social robots. In particular, anthropomorphism has been studied importantly in social robot design, and many approaches have been attempted to anthropomorphize social robots to produce positive effects. However, there is a lack of research that systematically describes the mechanism by which anthropomorphism for social robots is formed. Most of the existing studies have focused on verifying the positive effects of the anthropomorphism of social robots on consumers. In addition, the formation of anthropomorphism of social robots may vary depending on the individual's motivation or temperament, but there are not many studies examining this. A vague understanding of anthropomorphism makes it difficult to derive design optimal points for shaping the anthropomorphism of social robots. The purpose of this study is to verify the mechanism by which the anthropomorphism of social robots is formed. This study confirmed the effect of the human-likeness of social robots(Within-subjects) and the construal level of consumers(Between-subjects) on the formation of anthropomorphism through an experimental study of 3×2 mixed design. Research hypotheses on the mechanism by which anthropomorphism is formed were presented, and the hypotheses were verified by analyzing data from a sample of 206 people. The first hypothesis in this study is that the higher the human-likeness of the robot, the higher the level of anthropomorphism for the robot. Hypothesis 1 was supported by a one-way repeated measures ANOVA and a post hoc test. The second hypothesis in this study is that depending on the construal level of consumers, the effect of human-likeness on the level of anthropomorphism will be different. First, this study predicts that the difference in the level of anthropomorphism as human-likeness increases will be greater under high construal condition than under low construal condition.Second, If the robot has no human-likeness, there will be no difference in the level of anthropomorphism according to the construal level. Thirdly,If the robot has low human-likeness, the low construal level condition will make the robot more anthropomorphic than the high construal level condition. Finally, If the robot has high human-likeness, the high construal levelcondition will make the robot more anthropomorphic than the low construal level condition. We performed two-way repeated measures ANOVA to test these hypotheses, and confirmed that the interaction effect of human-likeness and construal level was significant. Further analysis to specifically confirm interaction effect has also provided results in support of our hypotheses. The analysis shows that the human-likeness of the robot increases the level of anthropomorphism of social robots, and the effect of human-likeness on anthropomorphism varies depending on the construal level of consumers. This study has implications in that it explains the mechanism by which anthropomorphism is formed by considering the human-likeness, which is the design attribute of social robots, and the construal level of consumers, which is the way of thinking of individuals. We expect to use the findings of this study as the basis for design optimization for the formation of anthropomorphism in social robots.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.47-64
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• 2021

The global spread of COVID-19 around the world has not only affected many parts of our daily life but also has a huge impact on many areas, including the economy and society. As the number of confirmed cases and deaths increases, medical staff and the public are said to be experiencing psychological problems such as anxiety, depression, and stress. The collective tragedy that accompanies the epidemic raises fear and anxiety, which is known to cause enormous disruptions to the behavior and psychological well-being of many. Long-term negative emotions can reduce people's immunity and destroy their physical balance, so it is essential to understand the psychological state of COVID-19. This study suggests a method of monitoring medial news reflecting current days which requires striving not only for physical but also for psychological quarantine in the prolonged COVID-19 situation. Moreover, it is presented how an easier method of analyzing social media networks applies to those cases. The aim of this study is to assist health policymakers in fast and complex decision-making processes. News plays a major role in setting the policy agenda. Among various major media, news headlines are considered important in the field of communication science as a summary of the core content that the media wants to convey to the audiences who read it. News data used in this study was easily collected using "Bigkinds" that is created by integrating big data technology. With the collected news data, keywords were classified through text mining, and the relationship between words was visualized through semantic network analysis between keywords. Using the KrKwic program, a Korean semantic network analysis tool, text mining was performed and the frequency of words was calculated to easily identify keywords. The frequency of words appearing in keywords of articles related to COVID-19 emotions was checked and visualized in word cloud 'China', 'anxiety', 'situation', 'mind', 'social', and 'health' appeared high in relation to the emotions of COVID-19. In addition, UCINET, a specialized social network analysis program, was used to analyze connection centrality and cluster analysis, and a method of visualizing a graph using Net Draw was performed. As a result of analyzing the connection centrality between each data, it was found that the most central keywords in the keyword-centric network were 'psychology', 'COVID-19', 'blue', and 'anxiety'. The network of frequency of co-occurrence among the keywords appearing in the headlines of the news was visualized as a graph. The thickness of the line on the graph is proportional to the frequency of co-occurrence, and if the frequency of two words appearing at the same time is high, it is indicated by a thick line. It can be seen that the 'COVID-blue' pair is displayed in the boldest, and the 'COVID-emotion' and 'COVID-anxiety' pairs are displayed with a relatively thick line. 'Blue' related to COVID-19 is a word that means depression, and it was confirmed that COVID-19 and depression are keywords that should be of interest now. The research methodology used in this study has the convenience of being able to quickly measure social phenomena and changes while reducing costs. In this study, by analyzing news headlines, we were able to identify people's feelings and perceptions on issues related to COVID-19 depression, and identify the main agendas to be analyzed by deriving important keywords. By presenting and visualizing the subject and important keywords related to the COVID-19 emotion at a time, medical policy managers will be able to be provided a variety of perspectives when identifying and researching the regarding phenomenon. It is expected that it can help to use it as basic data for support, treatment and service development for psychological quarantine issues related to COVID-19.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.2
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• pp.215-235
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• 2024

As artificial intelligence (AI) technology is recognized as a key technology that will determine future national competitiveness, competition for AI technology and industry promotion policies in major countries is intensifying. This study aims to present implications for domestic policy making by analyzing the policies of major countries on the start-up of AI companies, which are the basis of the AI industry ecosystem. The top four countries and the EU for the number of new investment attraction companies in the 2023 AI Index announced by the HAI Research Institute at Stanford University in the United States were selected, The United States enacted the National AI Initiative Act (NAIIA) in 2021. Through this law, The US Government is promoting continued leadership in the United States in AI R&D, developing reliable AI systems in the public and private sectors, building an AI system ecosystem across society, and strengthening DB management and access to AI policies conducted by all federal agencies. In the 14th Five-Year (2021-2025) Plan and 2035 Long-term Goals held in 2021, China has specified AI as the first of the seven strategic high-tech technologies, and is developing policies aimed at becoming the No. 1 AI global powerhouse by 2030. The UK is investing in innovative R&D companies through the 'Future Fund Breakthrough' in 2021, and is expanding related investments by preparing national strategies to leap forward as AI leaders, such as the implementation plan of the national AI strategy in 2022. Israel is supporting technology investment in start-up companies centered on the Innovation Agency, and the Innovation Agency is leading mid- to long-term investments of 2 to 15 years and regulatory reforms for new technologies. The EU is strengthening its digital innovation hub network and creating the InvestEU (European Strategic Investment Fund) and AI investment fund to support the use of AI by SMEs. This study aims to contribute to analyzing the policies of major foreign countries in making AI company start-up policies and providing a basis for Korea's strategy search. The limitations of the study are the limitations of the countries to be analyzed and the failure to attempt comparative analysis of the policy environments of the countries under the same conditions.

• Journal of the Korean Society of Clothing and Textiles
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• v.30 no.12 s.159
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• pp.1697-1707
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• 2006

Relentless advances in information technology are constantly transforming market dynamics of the retail industry. RFID is an emerging innovative technology that can reduce labor costs, improve inventory control and increase sales by effective business processes. Apparel retailers need to recognize the benefits of RFID and identify critical success factors. By focusing on apparel retailers, this study attempts (1) to identify the reality of RFID associated with benefits; and (2) to prospect the implementation of RFID in apparel retailing. We conducted a focus group interview with selected six panels who were experts of retail industry in the United States to obtain data regarding RFID attributes. Content analysis was used to generate related excerpts and classify 31 attributes of RFID benefits from the meaningful 173 responses. For experience of RFID, retailers were familiar with RFID technology and expressed the belief that RFID basically would support an existing retail system for speed to markets. However, retailers addressed the level of experience with RFID technology that they were still in the early adoption stage among few innovative companies. The content analysis identified five dimensions of RFID benefits for apparel retailing: Visibility and Velocity, Revenue Enhancement, Customer Service, Security, and Employee Productivity. This result lends support to the belief that RFID has a significant potential to streamline supply chain management, store operation and customer service for apparel retailing. This study provides intellectual and managerial implications far practitioners and researchers by postulating the effective use of RFID in the apparel retail industry.

• Cartoon and Animation Studies
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• s.35
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• pp.209-226
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• 2014

Chinese cartoon industry lately was able to see a rapid development which changed cartoon creative personnel associated with increased production technology development, new technologies, government support policy and a variety of environments. It was likely to have high expectations for changes in the policy environment of the country supported the comic creators and authors to develop its own comic industry. The State Administration of Press, Publication, Radio, Film and Television of China promoted the production for the development of Chinese animation with "domestic little video about the development of the animation industry's opinion", and "documents Documents". Animation industrial base and animation education was established in institutions such as the organization one after another. In the meantime, the spread of Japanese comics picture on the creative activation admitted but their comic creation and activation was slump. It would produce that the creation of its traditional culture based activation strategy to built comics. Since 2004, It was well represented for the creators of the cartoon creation of the tradition and uniqueness of Chinese history. In the prior to 2004, comics and strategies was to be differentiated. Today, China is an important source of comic marked the fact that the tradition was recognized and it was further developed with combining creativity of the past and the present production system. Comic creators comic story of traditional culture were excavated in order to have a sense of awareness and modern. The difference between China Cartoon and comics in other Asian countries is true that cartoon story came out naturally in a traditional culture. In this study, It would lead in the future to allow directional presented for the digital cartoon making development policy awareness through the comic creation and production of new media content industry enabled to China. Now, in the new media industry for the development of China's neighboring countries coped with climate change for the active exchange of information. It poured out ceaseless technical development and a range of policies to support business expansion. New China Cartoon was leaped to re-fit the industry.

• Child Health Nursing Research
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• v.2 no.2
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• pp.45-57
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• 1996

A serious disease in a family influences the entire family member given the fact that the members closely interact with each other. Especially in terms of pediatric nursing, study on family gains importance as the need to care of families whose children with developmental disabilities and chronic disease This study was done based on The Resiliency Model of Family Adjustment and Adaptation(McCubbin, 1991) is intended to examine the stress of parents whose children suffer from cleft lip or /and cleft palate. It also helps them to cope with the stress and analyze the relationship between the stress and coping This study used Family Inventory of Life Events and Changes (FILE) and Coping Health Inventory for Parents(CHIP) for measuring family stress and coping. The two instruments are revised to fit the social and cultural environment of Korean culture. Data collection was done from April 18, 1996 to May 18, 1996 at 8 University medical centers located in Seoul. Those who answered questionnaires were 84 parents whose children have cleft lip or /and cleft palate. SPSS PC+ was used to analyze the data collotted. Programs used for data analysis were t-test, ANOVA, Pearson correlation coefficient. The study is summarized as follows .1. The average score of family stress is 10.46(percentage of the full score 24.90) and 'finance and business strains'(3.25), and 'intrafamily strains'(2.65) ranked the highest. The average score of family's coping is 1.93, which is close to the answer of' moderately helpful' and they are measured to put their utmost efforts to' intergration and cooperation of family and optimistic definition on the situation'. 2. There is no significant statistical correlation between the family stress and coping. 3. Mothers show more stress than fathers in the parts of 'illness and family care strains' and 'losses'(t〓-2.34, t〓-2.32, p<.05). 4. Fathers show more willingness to cope with the stress than mothers do in the parts of' seeking social support','self-esteem','emotional comfort' 5. Mothers are more stress than fathers in the parts of family stress and its coping with it by usual traits(t〓-2.78, p<.05). Parents with religion are measured to cope more willingly than those who are not 6. Income of a family shows positive correlationship with family coping (r〓.28, p<.05). The study shows that gender difference is significant variable in studying on family stress and coping. Mothers get more stress than fathers, which has much to do with the fact that they are in charge of raising children and keeping houseworks. Accordingly, managing family crisis and its survival can be induced by giving support for the mothers, studying fathers including the rest of the family members and giving nursing care and arbitration ; religious background is also considered to be one of the important factors in family stress , judging from the relationship between family income and family's coping, caring given to suffering children is needed on societal levels. The above considerations bring up the need to have a longitudinal study of children with congenital anomaly including cleft lip or /and cleft palate and their families about family stress and coping. Resiliency programs on family system and their effectiveness and the relationship between the enlarged families with social and cultural values reflecting Korean tradition are also needed to be studied.

• Korean Journal of Heritage: History & Science
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• v.36
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• pp.347-377
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• 2003

China is a country with large agricultural areas and subject to frequent calamities. Drought is the top of them. It has been a key problem for development of agriculture in the country. In the long struggle against drought, Chinese have accumulated many rational and irrational experiences. The Dragon Kings Belief, which is popular in North China and discussed in a thesis, is one of their irrational experiences. The belief was passed together with Buddhism from India to China in the Tang Dynasty. After it settled down, it was incorporated with the local five dragons belief and a set of beliefs in dragon kings came into existence. The emergence of the dragon kings belief ended the history that the title of rain got was not clear in China and Dragon kings finally got the status. Irrigation is the lifeblood of agriculture in China. In a Chinese mind, Dragon kings are the most important gods who take charge of rain and thus offer the lifeblood. In understanding the nature and characteristics of Chinese traditional culture, it is important for us to make clear the origin and evolution of the belief, find out its nature, function and operation. In the every year beginning of February of the Fanzhuang calendar in the people of Hebeisheng Zhaoxian, would all hold a festival to offer sacrifices to the $^{{\circ}TM}^{\prime}longpai$. Longpai was regarded as the core of the temple fair, thus the native sons came to call this festival; "longpaihui". In this region the'Fanzhuang longpaihui'developed into a well knownand grand temple fair. It was able to attract numerous pilgrims with its special magic power, occupying a place in $China^{{\circ}TM}$ 'eryueer'festival with festive dragon activities. The dragon is a common totem among Chinese nationals. The belief worship of the dragon dates from the start time of primitive societies. Dragon oneself the ancients worship's thunder lightning. In the worship of the great universe, at first afterwards this belief with the tribe's totem worships to combine to become the animal spirit. In ancient myths legends, along with folk religion and beliefs all hold a very important position. The longpaihui is a temple fair without a temple; this characteristic is a distinction between longpaihui and other temple fairs. As for longpaihui must of the early historical records are unclear. The originator of a huitou system has a kind of organized form of the special features rather, originator of a huitou not fix constant, everything follows voluntarily principle, can become member with the freedom, also can back at any time the meeting. There is a longpaihui for 'dangjiaren', is total representative director in the originator of a huitou will. 'banghui' scope particularly for extensive, come apparently every kind of buildup that help can return into the banghui, where is the person of this village or outside village of, the general cent in banghui work is clear and definite, for longpaihui would various businesses open smoothly the exhibition provides to guarantees powerfully. Fanzhuang longpaihui from the beginning of February to beginning six proceed six days totally. The longpai is used as the ancestry absolute being to exsits with the community absolute being at the same time in fanzhuang first took civil faith, in reality is a kind of method to support social machine in native folks realize together that local community that important function, it provided a space, a kind of a view to take with a relation, rising contact, communication, solidify the community contents small village, formation with fanzhuang. The fanzhuang is used as supplies for gathering town, by luck too is this local community trade exchanges center at the same time therefore can say the faith of the longpai, in addition to its people's custom, religious meaning, still have got the important and social function. Moreover matter worthy of mentioning, Longpai would in organize process, from prepare and plan the producing of meeting every kind of meeting a longpeng of the matter do, all letting person feeling is to adjust the popular support of, get the mass approbation with positive participate. Apart from the originator of a huitou excluding, those although not originator of a huitou, however enthusiasm participate the banghui of its business, also is too much for the number.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.169-196
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• 2017

The fourth industrial revolution represents a revolutionary change in the business environment and its ecosystem, which is a fusion of Information Technology (IT) and other industries. In line with these recent changes, the Ministry of Employment and Labor of South Korea announced 'the Fourth Industrial Revolution Leader Training Program,' which includes five key support areas such as (1) smart manufacturing, (2) Internet of Things (IoT), (3) big data including Artificial Intelligence (AI), (4) information security, and (5) bio innovation. Based on this program, we can get a glimpse of the South Korean government's efforts and willingness to emit leading human resource with advanced IT knowledge in various fusion technology-related and newly emerging industries. On the other hand, in order to nurture excellent IT manpower in preparation for the fourth industrial revolution, the role of educational institutions capable of providing high quality IT education services is most of importance. However, these days, most IT educational institutions have had difficulties in providing customized IT education services that meet the needs of consumers (i.e., learners), without breaking away from the traditional framework of providing supplier-oriented education services. From previous studies, it has been found that the provision of customized education services centered on learners leads to high satisfaction of learners, and that higher satisfaction increases not only task performance and the possibility of business application but also learners' recommendation intention. However, since research has not yet been conducted in a comprehensive way that consider both antecedent and consequent factors of the learner's satisfaction, more empirical research on this is highly desirable. With the advent of the fourth industrial revolution, a rising interest in various convergence technologies utilizing information technology (IT) has brought with the growing realization of the important role played by IT-related education services. However, research on the role of IT education service quality in the context of IT education is relatively scarce in spite of the fact that research on general education service quality and satisfaction has been actively conducted in various contexts. In this study, therefore, the five dimensions of IT education service quality (i.e., tangibles, reliability, responsiveness, assurance, and empathy) are derived from the context of IT education, based on the SERVPERF model and related previous studies. In addition, the effects of these detailed IT education service quality factors on learners' educational satisfaction and their work application/recommendation intentions are examined. Furthermore, the moderating roles of learner position (i.e., practitioner group vs. manager group) and participation motivation (i.e., voluntary participation vs. involuntary participation) in relationships between IT education service quality factors and learners' educational satisfaction, work application intention, and recommendation intention are also investigated. In an analysis using the structural equation model (SEM) technique based on a questionnaire given to 203 participants of IT education programs in an 'M' IT educational institution in Seoul, South Korea, tangibles, reliability, and assurance were found to have a significant effect on educational satisfaction. This educational satisfaction was found to have a significant effect on both work application intention and recommendation intention. Moreover, it was discovered that learner position and participation motivation have a partial moderating impact on the relationship between IT education service quality factors and educational satisfaction. This study holds academic implications in that it is one of the first studies to apply the SERVPERF model (rather than the SERVQUAL model, which has been widely adopted by prior studies) is to demonstrate the influence of IT education service quality on learners' educational satisfaction, work application intention, and recommendation intention in an IT education environment. The results of this study are expected to provide practical guidance for IT education service providers who wish to enhance learners' educational satisfaction and service management efficiency.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.147-168
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• 2017

There have been many studies on accurate stock market forecasting in academia for a long time, and now there are also various forecasting models using various techniques. Recently, many attempts have been made to predict the stock index using various machine learning methods including Deep Learning. Although the fundamental analysis and the technical analysis method are used for the analysis of the traditional stock investment transaction, the technical analysis method is more useful for the application of the short-term transaction prediction or statistical and mathematical techniques. Most of the studies that have been conducted using these technical indicators have studied the model of predicting stock prices by binary classification - rising or falling - of stock market fluctuations in the future market (usually next trading day). However, it is also true that this binary classification has many unfavorable aspects in predicting trends, identifying trading signals, or signaling portfolio rebalancing. In this study, we try to predict the stock index by expanding the stock index trend (upward trend, boxed, downward trend) to the multiple classification system in the existing binary index method. In order to solve this multi-classification problem, a technique such as Multinomial Logistic Regression Analysis (MLOGIT), Multiple Discriminant Analysis (MDA) or Artificial Neural Networks (ANN) we propose an optimization model using Genetic Algorithm as a wrapper for improving the performance of this model using Multi-classification Support Vector Machines (MSVM), which has proved to be superior in prediction performance. In particular, the proposed model named GA-MSVM is designed to maximize model performance by optimizing not only the kernel function parameters of MSVM, but also the optimal selection of input variables (feature selection) as well as instance selection. In order to verify the performance of the proposed model, we applied the proposed method to the real data. The results show that the proposed method is more effective than the conventional multivariate SVM, which has been known to show the best prediction performance up to now, as well as existing artificial intelligence / data mining techniques such as MDA, MLOGIT, CBR, and it is confirmed that the prediction performance is better than this. Especially, it has been confirmed that the 'instance selection' plays a very important role in predicting the stock index trend, and it is confirmed that the improvement effect of the model is more important than other factors. To verify the usefulness of GA-MSVM, we applied it to Korea's real KOSPI200 stock index trend forecast. Our research is primarily aimed at predicting trend segments to capture signal acquisition or short-term trend transition points. The experimental data set includes technical indicators such as the price and volatility index (2004 ~ 2017) and macroeconomic data (interest rate, exchange rate, S&P 500, etc.) of KOSPI200 stock index in Korea. Using a variety of statistical methods including one-way ANOVA and stepwise MDA, 15 indicators were selected as candidate independent variables. The dependent variable, trend classification, was classified into three states: 1 (upward trend), 0 (boxed), and -1 (downward trend). 70% of the total data for each class was used for training and the remaining 30% was used for verifying. To verify the performance of the proposed model, several comparative model experiments such as MDA, MLOGIT, CBR, ANN and MSVM were conducted. MSVM has adopted the One-Against-One (OAO) approach, which is known as the most accurate approach among the various MSVM approaches. Although there are some limitations, the final experimental results demonstrate that the proposed model, GA-MSVM, performs at a significantly higher level than all comparative models.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.127-138
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• 2011

The core service of most research portal sites is providing relevant research papers to various researchers that match their research interests. This kind of service may only be effective and easy to use when a user can provide correct and concrete information about a paper such as the title, authors, and keywords. However, unfortunately, most users of this service are not acquainted with concrete bibliographic information. It implies that most users inevitably experience repeated trial and error attempts of keyword-based search. Especially, retrieving a relevant research paper is more difficult when a user is novice in the research domain and does not know appropriate keywords. In this case, a user should perform iterative searches as follows : i) perform an initial search with an arbitrary keyword, ii) acquire related keywords from the retrieved papers, and iii) perform another search again with the acquired keywords. This usage pattern implies that the level of service quality and user satisfaction of a portal site are strongly affected by the level of keyword management and searching mechanism. To overcome this kind of inefficiency, some leading research portal sites adopt the association rule mining-based keyword recommendation service that is similar to the product recommendation of online shopping malls. However, keyword recommendation only based on association analysis has limitation that it can show only a simple and direct relationship between two keywords. In other words, the association analysis itself is unable to present the complex relationships among many keywords in some adjacent research areas. To overcome this limitation, we propose the hybrid approach for establishing association network among keywords used in research papers. The keyword association network can be established by the following phases : i) a set of keywords specified in a certain paper are regarded as co-purchased items, ii) perform association analysis for the keywords and extract frequent patterns of keywords that satisfy predefined thresholds of confidence, support, and lift, and iii) schematize the frequent keyword patterns as a network to show the core keywords of each research area and connecting keywords among two or more research areas. To estimate the practical application of our approach, we performed a simple experiment with 600 keywords. The keywords are extracted from 131 research papers published in five prominent Korean journals in 2009. In the experiment, we used the SAS Enterprise Miner for association analysis and the R software for social network analysis. As the final outcome, we presented a network diagram and a cluster dendrogram for the keyword association network. We summarized the results in Section 4 of this paper. The main contribution of our proposed approach can be found in the following aspects : i) the keyword network can provide an initial roadmap of a research area to researchers who are novice in the domain, ii) a researcher can grasp the distribution of many keywords neighboring to a certain keyword, and iii) researchers can get some idea for converging different research areas by observing connecting keywords in the keyword association network. Further studies should include the following. First, the current version of our approach does not implement a standard meta-dictionary. For practical use, homonyms, synonyms, and multilingual problems should be resolved with a standard meta-dictionary. Additionally, more clear guidelines for clustering research areas and defining core and connecting keywords should be provided. Finally, intensive experiments not only on Korean research papers but also on international papers should be performed in further studies.