• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.49-67
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• 2015

Recently, emerging the notion of big data and social media has led us to enter data's big bang. Social networking services are widely used by people around the world, and they have become a part of major communication tools for all ages. Over the last decade, as online social networking sites become increasingly popular, companies tend to focus on advanced social media analysis for their marketing strategies. In addition to social media analysis, companies are mainly concerned about propagating of negative opinions on social networking sites such as Facebook and Twitter, as well as e-commerce sites. The effect of online word of mouth (WOM) such as product rating, product review, and product recommendations is very influential, and negative opinions have significant impact on product sales. This trend has increased researchers' attention to a natural language processing, such as a sentiment analysis. A sentiment analysis, also refers to as an opinion mining, is a process of identifying the polarity of subjective information and has been applied to various research and practical fields. However, there are obstacles lies when Korean language (Hangul) is used in a natural language processing because it is an agglutinative language with rich morphology pose problems. Therefore, there is a lack of Korean natural language processing resources such as a sentiment lexicon, and this has resulted in significant limitations for researchers and practitioners who are considering sentiment analysis. Our study builds a Korean sentiment lexicon with collective intelligence, and provides API (Application Programming Interface) service to open and share a sentiment lexicon data with the public (www.openhangul.com). For the pre-processing, we have created a Korean lexicon database with over 517,178 words and classified them into sentiment and non-sentiment words. In order to classify them, we first identified stop words which often quite likely to play a negative role in sentiment analysis and excluded them from our sentiment scoring. In general, sentiment words are nouns, adjectives, verbs, adverbs as they have sentimental expressions such as positive, neutral, and negative. On the other hands, non-sentiment words are interjection, determiner, numeral, postposition, etc. as they generally have no sentimental expressions. To build a reliable sentiment lexicon, we have adopted a concept of collective intelligence as a model for crowdsourcing. In addition, a concept of folksonomy has been implemented in the process of taxonomy to help collective intelligence. In order to make up for an inherent weakness of folksonomy, we have adopted a majority rule by building a voting system. Participants, as voters were offered three voting options to choose from positivity, negativity, and neutrality, and the voting have been conducted on one of the largest social networking sites for college students in Korea. More than 35,000 votes have been made by college students in Korea, and we keep this voting system open by maintaining the project as a perpetual study. Besides, any change in the sentiment score of words can be an important observation because it enables us to keep track of temporal changes in Korean language as a natural language. Lastly, our study offers a RESTful, JSON based API service through a web platform to make easier support for users such as researchers, companies, and developers. Finally, our study makes important contributions to both research and practice. In terms of research, our Korean sentiment lexicon plays an important role as a resource for Korean natural language processing. In terms of practice, practitioners such as managers and marketers can implement sentiment analysis effectively by using Korean sentiment lexicon we built. Moreover, our study sheds new light on the value of folksonomy by combining collective intelligence, and we also expect to give a new direction and a new start to the development of Korean natural language processing.

• Journal of Veterinary Clinics
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• v.24 no.4
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• pp.542-549
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• 2007

During a designated period(Jan. 2003$\sim$Jun. 2006), a total of 2,051 biopsy and necropsy cases submitted to Veterinary Medical Teaching Hospital of Seoul National University and local practitioners were diagnosed as canine tumors based on microscopic evaluation in the Department of Veterinary Pathology, College of Veterinary Medicine, Seoul National University. Four hundred and twenty of 2,051 tumor specimens excluding mammary(883, 43.1%) and cutaneous(748, 36.5%) tumors were included in this retrospective study. They were composed of genital tumors(189, 45.0%) followed by alimentary(113, 26.9%), hematopoietic(52, 12.4%), urinary(20, 4.8%), bone & joint(15, 3.6%), ocular & otic(9, 2.1%), respiratory(6, 1.4%), endocrine(6, 1.4%), and miscellaneous(10, 2.4%). Particular top ten tumor most frequently diagnosed were seminoma(48, 11.4%) followed by fibrous epulis(38, 9.0%), lymphoma(38, 9.0%), leiomyoma(33, 7.9%), fibroma(26, 6.2%), ovarian cyst(19, 4.5%), melanoma(15, 3.6%), papilloma(14, 3.3%), cystic endometrial hyperplasia(13, 3.1%), granulosa cell tumor(13, 3.1%) in descending order comprising 257(61.2%). The affected age of the animals with ten frequent tumors ranged from 3 months to 17 years old with a mean of 9.2 years old(n=218). There were no significant sex prevalence except female leiomyoma. The top seven anatomical sites of tumors inclusive were gingiva(62, 14.8%), testis(61, 14.5%), ovary(48, 11.4%), vagina(40, 9.5%), uterus(36, 8.6%), lymph node(30, 7.1%), and spleen(21, 5.0%).

• Journal of Korea Society of Industrial Information Systems
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• v.5 no.3
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• pp.94-110
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• 2000

While most of the previous information technology adoption and diffusion researches focus the critical factors not on the organizational perspective but on the individual perspective based on the various reasons such as informational characteristics. This paper will try to analysis the adoption and diffusion factors of the Internet related technologies based on the organizational perspective. Nowadays, in especially, the evolving and fast diffusing Internet related technologies and the flourishing e-commerce applications pressure retail banks that prepare the new types of online payment systems to maintain their existing and new customer relationship and compete with their potential competitors in the coming market environments. In addition, while most previous researches only focus on the adoption of new information technologies, this paper not only analysis the adoption of innovational technology but also analysis the diffusion process in an organization, which encourage practitioners and researchers to reveal more detail and practical analysis of the innovational technology adoption and diffusion process in ann organizational setting. Based on the previous researches, there are several factor-category will be selected for this research: 1) organizational factor, 2) within banking industry factor, 3) non-banking industry factor, 4) customer acceptance factor, 5) government factor, and 6) the functionality of e-commerce systems factor. Finally, in this study, we assumed that the more sophisticated e-commerce adopting banks provide the more broad range of banking services in general. Thus, we develop the extended integrated technology diffusion model to provide empirical evidences to distinguish between adopters and non-adopters and explain the diffusion levels of e-commerce using the level of services provided via Internet to the customer in retail bank industry.

• Journal of Digital Convergence
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• v.19 no.12
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• pp.531-539
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• 2021

Given the rapid development of information and communication technology (ICT) and the deepening of the information gap phenomenon in the context of the COVID-19 pandemic, researchers and practitioners need to understand the changing perceptions of new phenomena such as COVID-19 information gap on the existing information-vulnerable population. In this study, an empirical analysis was performed with the digital information gap survey data in 2020 to understand the potential impact of COVID-19 on the information gap according to the information-vulnerable class. This study is to verify the effect of information gap, marginalized groups, gender, and major factors of information services (contents, social relations, life services, information production, networking, social participation, non-face-to-face services) on the change in perception of digital information technology after Corona. Hierarchical regression analysis was performed. As a result of the analysis, it was found that the higher the content, social relationship, life service, networking, and digital non-face-to-face service, the higher the change in perception of digital information technology after Corona. Therefore, in light of the evolving phenomenon of COVID-19, it is considered that the government needs to provide education and training to strengthen the capabilities of the information-vulnerable class in order to resolve the digital information gap.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.181-199
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• 2021

Recently, financial companies are promoting chatbot services in line with the reduction of branches and the expansion of non-face-to-face services. However, it is difficult to expand the chatbot services at once in the presence of technical limitations and constraints of internal and external environment. Therefore, it is necessary to analyze the various situations of chatbot service to preemptively identify problems that can occur in stages and seek solutions. This study conducted interviews with 12 field practitioners and researchers to examine the intentions and behaviors of financial chatbot service users and interpreted them using TPB. The study revealed the characteristics of 'feelings and attitudes' such as convenience or inconvenience from the chatbot experience, 'subjective norms' such as herd behavior or the yearning for empathy of others, and 'behavioral control' according to the recognition of difficulty or convenience of chatbot use process. This study shows that this characteristic can affect the intention and actual behavior of users to use chatbot service continuously. In the future research, it is necessary to empirically study specific intentions and influence factors for actual users.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.131-145
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• 2010

The framework for making a coordinated decision for large-scale facilities has become an important issue in supply chain(SC) management research. The competitive business environment requires companies to continuously search for the ways to achieve high efficiency and lower operational costs. In the areas of production/distribution planning, many researchers and practitioners have developedand evaluated the deterministic models to coordinate important and interrelated logistic decisions such as capacity management, inventory allocation, and vehicle routing. They initially have investigated the various process of SC separately and later become more interested in such problems encompassing the whole SC system. The accurate quotation of ATP(Available-To-Promise) plays a very important role in enhancing customer satisfaction and fill rate maximization. The complexity for intelligent manufacturing system, which includes all the linkages among procurement, production, and distribution, makes the accurate quotation of ATP be a quite difficult job. In addition to, many researchers assumed ATP model with integer time. However, in industry practices, integer times are very rare and the model developed using integer times is therefore approximating the real system. Various alternative models for an ATP system with time lags have been developed and evaluated. In most cases, these models have assumed that the time lags are integer multiples of a unit time grid. However, integer time lags are very rare in practices, and therefore models developed using integer time lags only approximate real systems. The differences occurring by this approximation frequently result in significant accuracy degradations. To introduce the ATP model with time lags, we first introduce the dynamic production function. Hackman and Leachman's dynamic production function in initiated research directly related to the topic of this paper. They propose a modeling framework for a system with non-integer time lags and show how to apply the framework to a variety of systems including continues time series, manufacturing resource planning and critical path method. Their formulation requires no additional variables or constraints and is capable of representing real world systems more accurately. Previously, to cope with non-integer time lags, they usually model a concerned system either by rounding lags to the nearest integers or by subdividing the time grid to make the lags become integer multiples of the grid. But each approach has a critical weakness: the first approach underestimates, potentially leading to infeasibilities or overestimates lead times, potentially resulting in excessive work-inprocesses. The second approach drastically inflates the problem size. We consider an optimized ATP system with non-integer time lag in supply chain management. We focus on a worldwide headquarter, distribution centers, and manufacturing facilities are globally networked. We develop a mixed integer programming(MIP) model for ATP process, which has the definition of required data flow. The illustrative ATP module shows the proposed system is largely affected inSCM. The system we are concerned is composed of a multiple production facility with multiple products, multiple distribution centers and multiple customers. For the system, we consider an ATP scheduling and capacity allocationproblem. In this study, we proposed the model for the ATP system in SCM using the dynamic production function considering the non-integer time lags. The model is developed under the framework suitable for the non-integer lags and, therefore, is more accurate than the models we usually encounter. We developed intelligent ATP System for this model using genetic algorithm. We focus on a capacitated production planning and capacity allocation problem, develop a mixed integer programming model, and propose an efficient heuristic procedure using an evolutionary system to solve it efficiently. This method makes it possible for the population to reach the approximate solution easily. Moreover, we designed and utilized a representation scheme that allows the proposed models to represent real variables. The proposed regeneration procedures, which evaluate each infeasible chromosome, makes the solutions converge to the optimum quickly.

• Asia pacific journal of information systems
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• v.19 no.4
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• pp.77-100
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• 2009

Information Systems (IS) is an essential tool for any organizations. The last decade has seen an increasing body of knowledge on IS usage. Yet, IS often fails because of its misuse or non-use. In general, decisions regarding the selection of a system, which involve the evaluation of many IS vendors and an enormous initial investment, are made not through the consensus of employees but through the top-down decision making by top managers. In situations where the selected system does not satisfy the needs of the employees, the forced use of the selected IS will only result in their resistance to it. Many organizations have been either integrating dispersed legacy systems such as archipelago or adopting a new ERP (Enterprise Resource Planning) system to enhance employee efficiency. This study examines user resistance prior to the adoption of the selected IS or ERP system. As such, this study identifies the importance of managing organizational resistance that may appear in the pre-adoption context of an integrated IS or ERP system, explores key factors influencing user resistance, and investigates how prior experience with other integrated IS or ERP systems may change the relationship between the affecting factors and user resistance. This study focuses on organizational members' resistance and the affecting factors in the pre-adoption context of an integrated IS or ERP system rather than in the context of an ERP adoption itself or ERP post-adoption. Based on prior literature, this study proposes a research model that considers six key variables, including perceived benefit, system complexity, fitness with existing tasks, attitude toward change, the psychological reactance trait, and perceived IT competence. They are considered as independent variables affecting user resistance toward an integrated IS or ERP system. This study also introduces the concept of prior experience (i.e., whether a user has prior experience with an integrated IS or ERP system) as a moderating variable to examine the impact of perceived benefit and attitude toward change in user resistance. As such, we propose eight hypotheses with respect to the model. For the empirical validation of the hypotheses, we developed relevant instruments for each research variable based on prior literature and surveyed 95 professional researchers and the administrative staff of the Korea Photonics Technology Institute (KOPTI). We examined the organizational characteristics of KOPTI, the reasons behind their adoption of an ERP system, process changes caused by the introduction of the system, and employees' resistance/attitude toward the system at the time of the introduction. The results of the multiple regression analysis suggest that, among the six variables, perceived benefit, complexity, attitude toward change, and the psychological reactance trait significantly influence user resistance. These results further suggest that top management should manage the psychological states of their employees in order to minimize their resistance to the forced IS, even in the new system pre-adoption context. In addition, the moderating variable-prior experience was found to change the strength of the relationship between attitude toward change and system resistance. That is, the effect of attitude toward change in user resistance was significantly stronger in those with prior experience than those with no prior experience. This result implies that those with prior experience should be identified and provided with some type of attitude training or change management programs to minimize their resistance to the adoption of a system. This study contributes to the IS field by providing practical implications for IS practitioners. This study identifies system resistance stimuli of users, focusing on the pre-adoption context in a forced ERP system environment. We have empirically validated the proposed research model by examining several significant factors affecting user resistance against the adoption of an ERP system. In particular, we find a clear and significant role of the moderating variable, prior ERP usage experience, in the relationship between the affecting factors and user resistance. The results of the study suggest the importance of appropriately managing the factors that affect user resistance in organizations that plan to introduce a new ERP system or integrate legacy systems. Moreover, this study offers to practitioners several specific strategies (in particular, the categorization of users by their prior usage experience) for alleviating the resistant behaviors of users in the process of the ERP adoption before a system becomes available to them. Despite the valuable contributions of this study, there are also some limitations which will be discussed in this paper to make the study more complete and consistent.

• Journal of the Korea Convergence Society
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• v.9 no.8
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• pp.95-100
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• 2018

The Korea Convergence Society. The aim of this study was to evaluate the association between alcohol consumption and periodontal diseases in Korea adults. The date from the 2014 Korean National Health and Nutrition Survey were used, and 4,328 subjects over 30 years were included in the analysis. Periodontal disease was assessed using the Community Periodontal Index. The adjusted odds ratio of drinking experience, drinking frequency, the drinking amount and the drinking duration were calculated from the logistic regression model with the never-drinkers as a reference group and the logistic model controlled for age, gender, education, and diabetes. This study found that the risk of periodontal disease according to the drinking status of adults over 30 years of age was 1.39 times (95% CI=1.01-1.90) higher than that of non-drinking group when the number of drinks consumed at one time was more than seven glasses. The frequency of binge alcohol consumption, amount of alcohol consumption and duration of alcohol consumption were significantly associated with the risk of periodontal disease in a dose-response pattern among over 30 years. Alcohol consumption was discovered to be a potential risk indicator for periodontitis. Dental practitioners need to be aware that patients who drink may be at higher risk of periodontitis and could benefit from advice to quit drinking and maintain regular dental visits.

• Information Systems Review
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• v.10 no.1
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• pp.135-164
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• 2008

This research is to offer a structured yet practical ex-ante evaluation methodology for IT investment. Benchmarking the best practices of four Korean organizations, we try to integrate core processes, relevant measures, and evaluation dimensions into a consistent and wholesome body of evaluating methodology. The best practices we considered encompass a wide range of business enterprises, including for-profit, non-profit, service-oriented, and manufacturing entities. The proposed methodology consists of three stages; the first stage checks the validity of investments by looking into comprehensiveness of planning, willingness to accomplish, justifiable grounds for the investments, overlapping investments, and obstructing risks; the second do so by putting an IT investment into economic, strategic, and technological perspectives; and the last third would produce a unified quantity that summarizes outcome of the previous stages. Incorporating the proven knowledge, guidelines, and quantifying tools, the methodology could make a valuable reference model for IT evaluation practitioners who have been bedeviled by having to going through such ex-ante evaluations.

• The Korean Journal of Nuclear Medicine
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• v.27 no.2
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• pp.239-247
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• 1993

Differentiating the various causes of hydronephrosis from that of obstruction can be very difficult. The decision-making process for those instances of urinary tract dilatation that require surgical correction and those that do not is based in part on the findings of diuresis renography. The methodology for performing this test has differed among nuclear medicine practitioners and the surgical findings are occasionally discrepant from the diuretic renogram interpretation. Consequently we made an automatic computer software program that calculates the slope of the response curve. The quantitative indices, such as the injection and response t1/2 by linear-fitting and monoexponential-fitting, were compared with the visual assessment of the diuretic cinerenography and clinical outcome in 50 children (62 kidneys) with ureteropelvic junction obstruction. Pooled diuresis renogram data indicated that: (1) Visual evaluation of the diuretic cinerenography is a sensitive (87%, 54/62) tool to differentiate obstruction in suspected ureteropelvic junction obstruction. (2) The cut-off value (maximum washout t1/2 with non-obstruction) of injection and response t1/2 by linear-fitting were 40 min. (3) The sensitivity and specificity using injection and response t1/2 by linear-fitting for obstruction were 89%(23/26) and 100%(30/30), respectively. (4) Response t1/2 as well as injection t1/2 by monoexponential-fitting do not stratify children with possible ureteropelivic junction obstruction. In conclusion, quantitative assessment of diuretic renography as well as visual assessment of diuretic cinerenography correlate well with surgical and clinical outcome of suspected ureteropelvic junction obstruction.