• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.23-46
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• 2021

Collaborative filtering, which is often used in personalization recommendations, is recognized as a very useful technique to find similar customers and recommend products to them based on their purchase history. However, the traditional collaborative filtering technique has raised the question of having difficulty calculating the similarity for new customers or products due to the method of calculating similaritiesbased on direct connections and common features among customers. For this reason, a hybrid technique was designed to use content-based filtering techniques together. On the one hand, efforts have been made to solve these problems by applying the structural characteristics of social networks. This applies a method of indirectly calculating similarities through their similar customers placed between them. This means creating a customer's network based on purchasing data and calculating the similarity between the two based on the features of the network that indirectly connects the two customers within this network. Such similarity can be used as a measure to predict whether the target customer accepts recommendations. The centrality metrics of networks can be utilized for the calculation of these similarities. Different centrality metrics have important implications in that they may have different effects on recommended performance. In this study, furthermore, the effect of these centrality metrics on the performance of recommendation may vary depending on recommender algorithms. In addition, recommendation techniques using network analysis can be expected to contribute to increasing recommendation performance even if they apply not only to new customers or products but also to entire customers or products. By considering a customer's purchase of an item as a link generated between the customer and the item on the network, the prediction of user acceptance of recommendation is solved as a prediction of whether a new link will be created between them. As the classification models fit the purpose of solving the binary problem of whether the link is engaged or not, decision tree, k-nearest neighbors (KNN), logistic regression, artificial neural network, and support vector machine (SVM) are selected in the research. The data for performance evaluation used order data collected from an online shopping mall over four years and two months. Among them, the previous three years and eight months constitute social networks composed of and the experiment was conducted by organizing the data collected into the social network. The next four months' records were used to train and evaluate recommender models. Experiments with the centrality metrics applied to each model show that the recommendation acceptance rates of the centrality metrics are different for each algorithm at a meaningful level. In this work, we analyzed only four commonly used centrality metrics: degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality. Eigenvector centrality records the lowest performance in all models except support vector machines. Closeness centrality and betweenness centrality show similar performance across all models. Degree centrality ranking moderate across overall models while betweenness centrality always ranking higher than degree centrality. Finally, closeness centrality is characterized by distinct differences in performance according to the model. It ranks first in logistic regression, artificial neural network, and decision tree withnumerically high performance. However, it only records very low rankings in support vector machine and K-neighborhood with low-performance levels. As the experiment results reveal, in a classification model, network centrality metrics over a subnetwork that connects the two nodes can effectively predict the connectivity between two nodes in a social network. Furthermore, each metric has a different performance depending on the classification model type. This result implies that choosing appropriate metrics for each algorithm can lead to achieving higher recommendation performance. In general, betweenness centrality can guarantee a high level of performance in any model. It would be possible to consider the introduction of proximity centrality to obtain higher performance for certain models.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.129-142
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• 2016

Customer product reviews have become one of the important factors for purchase decision makings. Customers believe that reviews written by others who have already had an experience with the product offer more reliable information than that provided by sellers. However, there are too many products and reviews, the advantage of e-commerce can be overwhelmed by increasing search costs. Reading all of the reviews to find out the pros and cons of a certain product can be exhausting. To help users find the most useful information about products without much difficulty, e-commerce companies try to provide various ways for customers to write and rate product reviews. To assist potential customers, online stores have devised various ways to provide useful customer reviews. Different methods have been developed to classify and recommend useful reviews to customers, primarily using feedback provided by customers about the helpfulness of reviews. Most shopping websites provide customer reviews and offer the following information: the average preference of a product, the number of customers who have participated in preference voting, and preference distribution. Most information on the helpfulness of product reviews is collected through a voting system. Amazon.com asks customers whether a review on a certain product is helpful, and it places the most helpful favorable and the most helpful critical review at the top of the list of product reviews. Some companies also predict the usefulness of a review based on certain attributes including length, author(s), and the words used, publishing only reviews that are likely to be useful. Text mining approaches have been used for classifying useful reviews in advance. To apply a text mining approach based on all reviews for a product, we need to build a term-document matrix. We have to extract all words from reviews and build a matrix with the number of occurrences of a term in a review. Since there are many reviews, the size of term-document matrix is so large. It caused difficulties to apply text mining algorithms with the large term-document matrix. Thus, researchers need to delete some terms in terms of sparsity since sparse words have little effects on classifications or predictions. The purpose of this study is to suggest a better way of building term-document matrix by deleting useless terms for review classification. In this study, we propose neutrality index to select words to be deleted. Many words still appear in both classifications - useful and not useful - and these words have little or negative effects on classification performances. Thus, we defined these words as neutral terms and deleted neutral terms which are appeared in both classifications similarly. After deleting sparse words, we selected words to be deleted in terms of neutrality. We tested our approach with Amazon.com's review data from five different product categories: Cellphones & Accessories, Movies & TV program, Automotive, CDs & Vinyl, Clothing, Shoes & Jewelry. We used reviews which got greater than four votes by users and 60% of the ratio of useful votes among total votes is the threshold to classify useful and not-useful reviews. We randomly selected 1,500 useful reviews and 1,500 not-useful reviews for each product category. And then we applied Information Gain and Support Vector Machine algorithms to classify the reviews and compared the classification performances in terms of precision, recall, and F-measure. Though the performances vary according to product categories and data sets, deleting terms with sparsity and neutrality showed the best performances in terms of F-measure for the two classification algorithms. However, deleting terms with sparsity only showed the best performances in terms of Recall for Information Gain and using all terms showed the best performances in terms of precision for SVM. Thus, it needs to be careful for selecting term deleting methods and classification algorithms based on data sets.

• The Korean Journal of Elementary Counseling
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• v.8 no.1
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• pp.33-50
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• 2009

The purpose of this study was to develop a PBL-based career education program and to examine its effectiveness on school children's career maturity. It's specifically meant to prepare a career education program to assist students to get an accurate grip on their aptitude, interest and personality and explore various sorts of occupations in the course of solving authentic and contextual career-related problems. After children's developmental characteristics and needs were analyzed, task analysis was implemented, and the objectives were defined. And then the core of the program, PBL problems were developed, and the validity of the problems were verified Evaluation plans and tools were prepared to assess children's problem-solving process and presentation, and an online learning space was designed. The program that consisted of 10-minute 21 sessions was provided to fifth-grade elementary schoolers for eight weeks. The findings of the study were as follows: The experimental group that participated in the PBL-based career education program showed a more significant improvement than the control group that didn't in career attitude and three career attitude subfactors involving planness, disposition and compromise. And the former made a more significant progress than the latter in career ability and its subfactors including vocational comprehension, self-understanding and decision-making skills as well. As a result of making a content analysis to make up for the survey, the students reported that they were able to get an objective understanding of themselves and acquire diverse and profound knowledge on work and the business world in the middle of solving the given PBL problems related to different areas in group and giving a presentation. In conclusion, a PBL based career education program developed by this researcher encouraged the students to have an objective self-understanding, to have a dynamic interactive discussion with their group members. Therefore the program had a positive impact on boosting the career attitude and career ability of the elementary schoolers. The findings suggested that in the field of elementary career education, autonomous learning attitude and subjecthood are the crucial factors to stimulate school children to explore and create their own future.

• The Korean Society of Law and Medicine
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• v.15 no.1
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• pp.335-373
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• 2014

According to one Medicare report, in the US, total federal spending on health care expends almost 18 percent of the nation's GDP, about double what most industrialized nations spend on health care. And in 2011, Medicare spending reached close to $554 billion, which amounted to 21 percent of the total spent on U.S. health care in that year. Of that $554 billion, Medicare spent 28 percent, or about $170 billion, on patients' last six months of life. So what are the reasons of this high cost in EOL care and its possible solutions? Much spendings of Medicare on End-of-Life care for the terminally ill/chronically ill in the US has led health economics experts to assess the characteristics of the care. Decades of study shows that EOL care is usually supply-sensitive and poor in cost-effectiveness. The volume of care is sensitively depending on the supply of resources, rather than the severity of illness or preferences of patients. This means at the End-of-Life care, the medical resources are being overused. On the other hand, opposed to the common assumption, "The more care the better utility", the study shows that the outcome is very poor. Actually the patient preference and concerns are quite the opposite from what intense EOL care would bring about. This study analyzes the reasons for the supply-sensitiveness of EOL care. It can be resulted from the common misconception about the intense care and the outcome, physicians' mission for patients, lack of End-of-Life Care Decision which helps the patients choose their own preferred treatment intensity. It also could be resulted from physicians' fear of legal liabilities, and the management strategy since the hospitals are also seeking for financial benefits. This study suggests the possible solutions for over-treatment at the End-of-Life resulting from supply-sensitiveness. Solutions can be sought in two aspects, legal implementation and management strategy. In order to implement advance directive properly, active ethics education for physicians to change their attitude toward EOL care and more conversations about end-of-life care between physicians and patients is crucial, and incentive system for the physicians who actively have the conversations with patients will also help. Also, the general education towards the public is also important in the long run, and easy and official advance directive registry system-such as online registry-has to be built and utilized more widely. Alternative strategies in management are also needed. For example, the new strategic cost management and management education, such as cutting unnecessary costs and resetting values as medical providers have to be considered. In order to effectively resolve the problem in EOL care for the terminally ill/chronically ill and provide better experience to the patients, first of all, the misconception and the wrong conventional wisdom among doctors, patients, and the government have to be overcome. And then there should be improvements in systems and cultures of the EOL care.

• Asia pacific journal of information systems
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• v.21 no.4
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• pp.45-62
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• 2011

The notion of information systems (IS) continuance has recently emerged as one of the most important research issues in the field of IS. A great deal of research has been conducted thus far on the basis of theories adapted from various disciplines including consumer behaviors and social psychology, in addition to theories regarding information technology (IT) acceptance. This previous body of knowledge provides a robust research framework that can already account for the determination of IS continuance; however, this research points to other, thus-far-unelucidated determinant factors such as habit, which were not included in traditional IT acceptance frameworks, and also re-emphasizes the importance of emotion-related constructs such as satisfaction in addition to conscious intention with rational beliefs such as usefulness. Experiences should also be considered one of the most important factors determining the characteristics of information system (IS) continuance and the features distinct from those determining IS acceptance, because more experienced users may have more opportunities for IS use, which would allow them more frequent use than would be available to less experienced or non-experienced users. Interestingly, experience has dual features that may contradictorily influence IS use. On one hand, attitudes predicated on direct experience have been shown to predict behavior better than attitudes from indirect experience or without experience; as more information is available, direct experience may render IS use a more salient behavior, and may also make IS use more accessible via memory. Therefore, experience may serve to intensify the relationship between IS use and conscious intention with evaluations, On the other hand, experience may culminate in the formation of habits: greater experience may also imply more frequent performance of the behavior, which may lead to the formation of habits, Hence, like experience, users' activation of an IS may be more dependent on habit-that is, unconscious automatic use without deliberation regarding the IS-and less dependent on conscious intentions, Furthermore, experiences can provide basic information necessary for satisfaction with the use of a specific IS, thus spurring the formation of both conscious intentions and unconscious habits, Whereas IT adoption Is a one-time decision, IS continuance may be a series of users' decisions and evaluations based on satisfaction with IS use. Moreover. habits also cannot be formed without satisfaction, even when a behavior is carried out repeatedly. Thus, experiences also play a critical role in satisfaction, as satisfaction is the consequence of direct experiences of actual behaviors. In particular, emotional experiences such as enjoyment can become as influential on IS use as are utilitarian experiences such as usefulness; this is especially true in light of the modern increase in membership-based hedonic systems - including online games, web-based social network services (SNS), blogs, and portals-all of which attempt to provide users with self-fulfilling value. Therefore, in order to understand more clearly the role of experiences in IS continuance, analysis must be conducted under a research framework that includes intentions, habits, and satisfaction, as experience may not only have duration-based moderating effects on the relationship between both intention and habit and the activation of IS use, but may also have content-based positive effects on satisfaction. This is consistent with the basic assumptions regarding the determining factors in IS continuance as suggested by Oritz de Guinea and Markus: consciousness, emotion, and habit. The principal objective of this study was to explore and assess the effects of experiences in IS continuance, with special consideration given to conscious intentions and unconscious habits, as well as satisfaction. IN service of this goal, along with a review of the relevant literature regarding the effects of experiences and habit on continuous IS use, this study suggested a research model that represents the roles of experience: its moderating role in the relationships of IS continuance with both conscious intention and unconscious habit, and its antecedent role in the development of satisfaction. For the validation of this research model. Korean university student users of 'Cyworld', one of the most influential social network services in South Korea, were surveyed, and the data were analyzed via partial least square (PLS) analysis to assess the implications of this study. In result most hypotheses in our research model were statistically supported with the exception of one. Although one hypothesis was not supported, the study's findings provide us with some important implications. First the role of experience in IS continuance differs from its role in IS acceptance. Second, the use of IS was explained by the dynamic balance between habit and intention. Third, the importance of satisfaction was confirmed from the perspective of IS continuance with experience.

• Journal of Hospice and Palliative Care
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• v.21 no.1
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• pp.9-13
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• 2018

Purpose: The purpose of this study was to assess the factors influencing the rescue medication decisions for breakthrough cancer patients and evaluate treatments using the factors. Methods: Based on the results of an online survey conducted by the Korean Society of Hospice and Palliative Care from September 2014 through December 2014, we assessed the level of agreement on nine factors influencing rescue medication preference. The same factors were used to evaluate oral transmucosal fentanyl lozenge, oral oxycodone and intravenous morphine. Results: Agreed by 77 physicians, a rapid onset of action was the most important factor for their decision of rescue medication. Other important factors were easy administration, strong efficacy, predictable efficacy and less adverse effects. Participants agreed that intravenous morphine produced a rapid onset of action and strong and predictable efficacy and cited difficulty of administration and adverse effects as negative factors. Oral oxycodone was desirable in terms of easy administration and less adverse effects. However, its onset of action was slower than intravenous morphine. While many agreed to easy administration of oral transmucosal fentanyl lozenge, the level of agreement was low for strength and predictability of its efficacy, long-term durability and sleep improvement. Conclusion: Rapid onset of action is one of the important factors that influence physicians' selection of rescue medication. Physicians' assessment of rescue medication differed by medication.

• Management & Information Systems Review
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• v.38 no.4
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• pp.137-157
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• 2019

Companies are trying to use enterprise SNS for collaboration and speedy decision-making. This study verified the mediating effect of communication between enterprise SNS and job performance, and proved the moderating effect of nationality between enterprise SNS and communication. This study collected survey data of 81 Korean and 81 Chinese from employees who have used enterprise SNS in Korea and China. As results of data analysis, first, enterprise SNS improved job performance through speedy information sharing and error reduction. Second, communication mediated the effect of enterprise SNS on job performance. Third, enterprise SNS increased the level of organizational communication through decreasing the burden of offline face-to-face communication. Compared with Chinese corporate organizations, Korean corporate organizations have high power distances, centralized control, and high superior authority. Therefore, in the off-line communication situation, the subordinate feels the social pressure to follow the command of the superior. Thus communication is one-way and closed. In this Korean organizational situation, corporate SNS can be used as a means to bypass rigid offline communication. In the online communication environment of non face-to-face corporate SNS, anxiety and stress of face-to-face communication can be reduced, so communication between the upper and lower sides can flow more smoothly. The contribution of this paper is that it proved that enterprise SNS promotes communication and improve job performance by reducing the anxiety or stress of offline communication, while according to prior research successful adoption of many types of information systems requires the fit between an organization and its organizational culture.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.117-129
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• 2015

As the Internet becomes ubiquitous, a large volume of information is posted on the Internet with exponential growth every day. Accordingly, it is not unusual that investors in stock markets gather and compile firm-specific or market-wide information through online searches. Importantly, it becomes easier for investors to acquire value-relevant information for their investment decision with the help of powerful search tools on the Internet. Our study examines whether or not the Internet helps investors assess a firm's value better by using firm-level data over long periods spanning from January 2004 to December 2013. To this end, we construct weekly-based search volume for information technology (IT) services firms on the Internet. We limit our focus to IT firms since they are often equipped with intangible assets and relatively less recognized to the public which makes them hard-to measure. To obtain the information on those firms, investors are more likely to consult the Internet and use the information to appreciate the firms more accurately and eventually improve their investment decisions. Prior studies have shown that changes in search volumes can reflect the various aspects of the complex human behaviors and forecast near-term values of economic indicators, including automobile sales, unemployment claims, and etc. Moreover, search volume of firm names or stock ticker symbols has been used as a direct proxy of individual investors' attention in financial markets since, different from indirect measures such as turnover and extreme returns, they can reveal and quantify the interest of investors in an objective way. Following this line of research, this study aims to gauge whether the information retrieved from the Internet is value relevant in assessing a firm. We also use search volume for analysis but, distinguished from prior studies, explore its impact on return comovements with market returns. Given that a firm's returns tend to comove with market returns excessively when investors are less informed about the firm, we empirically test the value of information by examining the association between Internet searches and the extent to which a firm's returns comove. Our results show that Internet searches are negatively associated with return comovements as expected. When sample is split by the size of firms, the impact of Internet searches on return comovements is shown to be greater for large firms than small ones. Interestingly, we find a greater impact of Internet searches on return comovements for years from 2009 to 2013 than earlier years possibly due to more aggressive and informative exploit of Internet searches in obtaining financial information. We also complement our analyses by examining the association between return volatility and Internet search volumes. If Internet searches capture investors' attention associated with a change in firm-specific fundamentals such as new product releases, stock splits and so on, a firm's return volatility is likely to increase while search results can provide value-relevant information to investors. Our results suggest that in general, an increase in the volume of Internet searches is not positively associated with return volatility. However, we find a positive association between Internet searches and return volatility when the sample is limited to larger firms. A stronger result from larger firms implies that investors still pay less attention to the information obtained from Internet searches for small firms while the information is value relevant in assessing stock values. However, we do find any systematic differences in the magnitude of Internet searches impact on return volatility by time periods. Taken together, our results shed new light on the value of information searched from the Internet in assessing stock values. Given the informational role of the Internet in stock markets, we believe the results would guide investors to exploit Internet search tools to be better informed, as a result improving their investment decisions.

• Journal of Environmental Impact Assessment
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• v.28 no.5
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• pp.440-456
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• 2019

The controversy of the risk perception related to particulate matters becomes significant. Therefore, in order to understand the nature of the particulate matters, we gathered articles and comments in on-line community related to bicycling which is affected by exposure of the particulate matters. As a result, firstly, the government - led particulate matter policy was strengthened and segmented every period, butthe risk perception related to particulate matters in the bicycle community has become active and serious. Second, as a result of analyzing the perception change of outdoor activities related to particulate matters, bicycle users in community showed a tendency of outdoor activity depending on the degree of particulate matters ratherthan the weather. In addition, the level of the risk perception related to particulate matters has been moved from fears of serious threat in daily life and health, combined with the disregard of domestic particulate matter levels or mask performance. Ultimately, these risk perception related to particulate matters have led some of the bicycling that were mainly enjoyed outdoors to the indoor space. However, in comparison with outdoor bicycling enjoyed by various factors such as scenery, people, and weather, the monotonous indoor bicycling was converted into another type of indoor exercise such as fitness and yoga. In summary, it was derived from mistrust of excessive information or policy provided by the government or local governments. It is considered that environmental policy should be implemented after discussion of risk communication that can reduce the gap between public anxiety and concern so as to cope with the risk perception related to particulate matters. Therefore,this study should be provided as an academic basis for the effective communication direction when decision makers establish the policy related to particulate matters.

• The Korean Journal of Archival Studies
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• no.14
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• pp.153-190
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• 2006

Externally, business environment in public institution has being changed as government business reference model(BRM) appeared and business management systems for transparency of a policy decision process are introduced. After Records Automation System started its operation, dissatisfaction grows because of inadequacy in system function and the problems about authenticity of electronic records. With these backgrounds, National Archives and Records Service had carried out 'Information Strategy Planning for Reform to Records Management System' for 5 months from September, 2005. As result, this project reengineers current records management processes and presents the world-class system model. After Records and Archives Management Act was made, the records management in public institution has propelled the concept that paper records are handled by means of the electric data management. In this reformed model, however, we concentrates on the electric records, which have gradually replaced the paper records and investigate on the management methodology considering attributes of electric records. According to this new paradigm, the electric records management raises a new issue in the records management territory. As the major contents of the models connecting with electric records management were analyzed and their significance and bounds were closely reviewed, the aim of this paper is the understanding of the future bearings of the management system. Before the analysis of the reformed models, issues in new business environments and their records management were reviewed. The government's BRM and Business management system prepared the general basis that can manage government's whole results on the online and classify them according to its function. In this points, the model is innovative. However considering the records management, problems such as division into Records Classification, definitions and capturing methods of records management objects, limitations of Records Automation System and so on was identified. For solving these problems, the reformed models that has a records classification system based on the business classification, extended electronic records filing system, added functions for strengthening electric records management and so on was proposed. As regards dramatically improving the role of records center in public institution, searching for the basic management methodology of the records management object from various agency and introducing the detail design to keep documents' authenticity, this model forms the basis of the electric records management system. In spite of these innovations, however, the proposed system for real electric records management era is still in its beginning. In near feature, when the studies is concentrated upon the progress of qualified classifications, records capturing plans for foreign records structures such like administration information system, the further study of the previous preservation technology, the developed prospective of electric records management system will be very bright.