• Journal of the Korean Society for Library and Information Science
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• v.58 no.1
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• pp.99-122
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• 2024

This study investigated librarians' awareness of and demand for the librarian learning community in order to successfully introduce and operate the librarian learning community. For this purpose, an online survey was conducted targeting current librarians and a total of 474 responses were collected. The main analysis results are as follows. Firstly, librarians showed a very low awareness of the librarian learning community, while they highly evaluated the purpose and significance of such a community. Secondly, the motivations for librarians to participate in the librarian learning community were primarily focused on professional growth, solidarity with colleagues, and satisfaction of intellectual curiosity, in that order. Thirdly, the ultimate values of the librarian learning community were identified as improving library services, enhancing professionalism, fostering collaborative group exploration, sharing values and visions. Fourthly, the success factors of the librarian-learning community were ranked as follows: member voluntarism, a culture of collaboration among members, dedicated time (once a week), and a supportive environment (budget, space, etc.). On the other hand, the failure factors were identified as a lack of time due to heavy workloads, lack of member voluntarism, indifference from superiors, and insufficient support environment (budget, space, etc.). Finally, the willingness to participate is also very high. Furthermore, it was observed that there is a wide range of interests in various topics among librarians. The results of this study are expected to be useful as basic data for determining practical operation methods or selecting topics when operating a librarian learning community in the future.

• Information Systems Review
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• v.25 no.1
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• pp.111-128
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• 2023

With the development of artificial intelligence technology, interest in data-based product preference estimation and personalized recommender systems is increasing. However, if the recommendation is not suitable, there is a risk that it may reduce the purchase intention of the customer and even extend to a huge financial loss due to the characteristics of the financial product. Therefore, developing a recommender system that comprehensively reflects customer characteristics and product preferences is very important for business performance creation and response to compliance issues. In the case of financial products, product preference is clearly divided according to individual investment propensity and risk aversion, so it is necessary to provide customized recommendation service by utilizing accumulated customer data. In addition to using these customer behavioral characteristics and transaction history data, we intend to solve the cold-start problem of the recommender system, including customer demographic information, asset information, and stock holding information. Therefore, this study found that the model proposed deep learning-based collaborative filtering by deriving customer latent preferences through characteristic information such as customer investment propensity, transaction history, and financial product information based on customer transaction log records was the best. Based on the customer's financial investment mechanism, this study is meaningful in developing a service that recommends a high-priority group by establishing a recommendation model that derives expected preferences for untraded financial products through financial product transaction data.

• Journal of Korean Library and Information Science Society
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• v.55 no.2
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• pp.133-157
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• 2024

The purpose of this study is to obtain basic information necessary to set the content and direction of MIL cooperative teaching by analyzing elementary and secondary school teachers' MIL awareness and cooperative teaching experience. For this purpose, a survey was conducted on cooperative classes, media, and MIL among 401 teachers in the Gyeonggido Office of Education. The analysis results are as follows. ① It is necessary to provide teachers with the experience of cooperative classes and develop MIL cooperative class models and manuals, ② It is necessary to apply the MIL curriculum to school education and operate it as a cooperative classes, ③ The types of media used in the MIL curriculum should be developed by reflecting the development stage and the opinions of educational experts. ④ In the MIL curriculum, it is necessary to deal with 'information comprehension (reading) and evaluation competency education'. ⑤ It is necessary to use school libraries and teacher-librarians in promoting students' MIL improvement policies. As a follow-up study, it is necessary to conduct MIL cooperative instructional models and MIL curriculum studies.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.27 no.4
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• pp.258-265
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• 2024

Purpose: To date, there is no region-specific guideline for pediatric endoscopy training. This study aimed to illustrate the current status of pediatric endoscopy training in Asia-Pacific region and identify opportunities for improvement. Methods: A cross-sectional survey, using a standardized electronic questionnaire, was conducted among medical schools in the Asia-Pacific region in January 2024. Results: A total of 57 medical centers in 12 countries offering formal Pediatric Gastroenterology training programs participated in this regional survey. More than 75% of the centers had an average case load of <10 cases per week for both diagnostic and therapeutic endoscopies. Only 36% of the study programs employed competency-based outcomes for program development, whereas nearly half (48%) used volume-based curricula. Foreign body retrieval, polypectomy, percutaneous endoscopic gastrostomy, and esophageal variceal hemostasis, that is, sclerotherapy or band ligation (endoscopic variceal sclerotherapy and endoscopic variceal ligation), comprised the top four priorities that the trainees should acquire in the autonomous stage (unconscious) of competence. Regarding the learning environment, only 31.5% provided formal hands-on workshops/simulation training. The direct observation of procedural skills was the most commonly used assessment method. The application of a quality assurance (QA) system in both educational and patient care (Pediatric Endoscopy Quality Improvement Network) aspects was present in only 28% and 17% of the centers, respectively. Conclusion: Compared with Western academic societies, the limited availability of cases remains a major concern. To close this gap, simulation and adult endoscopy training are essential. The implementation of reliable and valid assessment tools and QA systems can lead to significant development in future programs.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.85-109
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• 2018

Recommender system recommends the items expected to be purchased by a customer in the future according to his or her previous purchase behaviors. It has been served as a tool for realizing one-to-one personalization for an e-commerce service company. Traditional recommender systems, especially the recommender systems based on collaborative filtering (CF), which is the most popular recommendation algorithm in both academy and industry, are designed to generate the items list for recommendation by using 'overall rating' - a single criterion. However, it has critical limitations in understanding the customers' preferences in detail. Recently, to mitigate these limitations, some leading e-commerce companies have begun to get feedback from their customers in a form of 'multicritera ratings'. Multicriteria ratings enable the companies to understand their customers' preferences from the multidimensional viewpoints. Moreover, it is easy to handle and analyze the multidimensional ratings because they are quantitative. But, the recommendation using multicritera ratings also has limitation that it may omit detail information on a user's preference because it only considers three-to-five predetermined criteria in most cases. Under this background, this study proposes a novel hybrid recommendation system, which selectively uses the results from 'traditional CF' and 'CF using multicriteria ratings'. Our proposed system is based on the premise that some people have holistic preference scheme, whereas others have composite preference scheme. Thus, our system is designed to use traditional CF using overall rating for the users with holistic preference, and to use CF using multicriteria ratings for the users with composite preference. To validate the usefulness of the proposed system, we applied it to a real-world dataset regarding the recommendation for POI (point-of-interests). Providing personalized POI recommendation is getting more attentions as the popularity of the location-based services such as Yelp and Foursquare increases. The dataset was collected from university students via a Web-based online survey system. Using the survey system, we collected the overall ratings as well as the ratings for each criterion for 48 POIs that are located near K university in Seoul, South Korea. The criteria include 'food or taste', 'price' and 'service or mood'. As a result, we obtain 2,878 valid ratings from 112 users. Among 48 items, 38 items (80%) are used as training dataset, and the remaining 10 items (20%) are used as validation dataset. To examine the effectiveness of the proposed system (i.e. hybrid selective model), we compared its performance to the performances of two comparison models - the traditional CF and the CF with multicriteria ratings. The performances of recommender systems were evaluated by using two metrics - average MAE(mean absolute error) and precision-in-top-N. Precision-in-top-N represents the percentage of truly high overall ratings among those that the model predicted would be the N most relevant items for each user. The experimental system was developed using Microsoft Visual Basic for Applications (VBA). The experimental results showed that our proposed system (avg. MAE = 0.584) outperformed traditional CF (avg. MAE = 0.591) as well as multicriteria CF (avg. AVE = 0.608). We also found that multicriteria CF showed worse performance compared to traditional CF in our data set, which is contradictory to the results in the most previous studies. This result supports the premise of our study that people have two different types of preference schemes - holistic and composite. Besides MAE, the proposed system outperformed all the comparison models in precision-in-top-3, precision-in-top-5, and precision-in-top-7. The results from the paired samples t-test presented that our proposed system outperformed traditional CF with 10% statistical significance level, and multicriteria CF with 1% statistical significance level from the perspective of average MAE. The proposed system sheds light on how to understand and utilize user's preference schemes in recommender systems domain.

• 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.

• Asia pacific journal of information systems
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• v.23 no.1
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• pp.45-63
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• 2013

The purpose of this research is on the identification of the effects of perceived interactivity formed by the electronic collaborative referral system on the organizational loyalty. Two channels through which the effects proceeded were investigated. One is the "system channel" which consists of "interactivity of the inter-organizational system ${\rightarrow}$ intention of using the system ${\rightarrow}$ organization loyalty" (hypothesis 1, 2), that is the channel which anticipates that a better understanding on the interactivity of the inter-organizational system makes the intention of the using the system strong, and this strong intention results the higher organization loyalty. The other is "organization channel" which consists of "interactivity of the inter-organizational system ${\rightarrow}$ perceived interactivity on the counterpart ${\rightarrow}$ perceived relation benefits with the counterpart ${\rightarrow}$ organization loyalty" (hypothesis 3, 4, 5). The channel means that as the perceived interactivity of users on the inter-organizational system becomes greater, the perceived interactivity with the counterpart is increasing. And this makes the users feel that more benefits can be obtained by the relationship with system providing organization, and finally makes the organization loyalty that is the intention to maintain the relationship greater. The corroborative evidence data confirm the two channels are obtained by questing on the electronic referral system of Samsung Medical Center to the doctors of the first and second collaborated hospitals or clinics, and by analyzing statistically. The verification result for the "system channel" showed that as the perception on the interactivity of inter-organizational system was increasing, the intention for consistent using increased(support hypothesis 1), and then the organization loyalty that is the relationship maintaining indication by using the referral system also increased(support hypothesis 2). And the confirmation result for the "organization channel" indicated that the perceptive interactivity on the counterpart increased as the understanding on the interactivity of inter-organizational system increased(support hypothesis 3), consecutively, with the intuitive relation benefits increase with the counterpart(support hypothesis 4) the organization loyalty means the intention to maintain the relationship was confirmed to increase(support hypothesis 5). These results demonstrate that when the perceived interactivity in using many systems at the collaboration between organizations is increasing, the positive image on the systems creates the consistent system using intention, and the positive image increases the wants for preserving the relationship with counter organization. In addition, the perceived interactivity of inter-organizational system users affects directly on the perceived interactivity of the counter organization, so the important role of inter-organizational system in promoting the interactivity between cooperative counterparts was recognized. And the perceived interactivity on the counter organization become greater, the influence on the perceived benefits from cooperation is positive. Therefore, the perceived interactivity by using inter-organizational system was confirmed as a prerequisite for the continuous relationship.

• Journal of the Korean Institute of Landscape Architecture
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• v.43 no.3
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• pp.92-100
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• 2015

Unlike most other planning processes, brownfield planning generally requires a high level of technical and legal expertise due to potential site contamination. To successfully engage in inclusionary decision making, an adaptive collaboration strategy for brownfield planning is therefore critical. This study examines how a communicative planning approach can be used to overcome the challenge of enabling experts from different fields to work alongside lay people from the local community to achieve a properly balanced collaboration in brownfield planning. After identifying appropriate indicators for collaboration through a literature review of established communicative planning theory, these indicators are applied to the brownfield planning process, highlighting critical points of collaboration such as site prioritization, assessment, remediation, and redevelopment throughout. The results suggest the critical need for an adaptive model focusing on three aspects: 1. Facilitation of a balanced dialogue between the experts with social, cultural, and design-based knowledge and the ones with scientific and engineering-based knowledge, 2. Preparation of an appropriate tool for risk communication with the lay people, 3. Development of decision support system for the integration of expert-oriented technical data and public opinion-oriented subjective data.

• Journal of Acupuncture Research
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• v.26 no.6
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• pp.121-132
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• 2009

Objectives : To evaluate the current status of East-West combination treatment in joint disorders. Methods : The medical records of patients who visited the Joints & Rheumatism Center at the Kyung Hee East-West Neo Medical Center from April 2006 to June 2009 were evaluated. The general characteristics of patients who underwent combination treatment, trend in number of cross-system referrals, and disorders and involved body regions of patients referred to the Eastern medical hospital from the Western medical hospital were initially assessed. 6 major disorders were found from the initial scanning. The trend in number of cross-hospital referrals, number of visits to the Eastern medical hospital, current status of combination treatment, treatment modality, and reason for cross-system referral was evaluated. Results : 1. 1510 patients were referred from the Eastern medical hospital to the Western medical hospital, and 1065 patients were referred from the Western medical hospital to the Eastern medical hospital. First visit patients reached a peak at the second quarter of 2007 and fourth quarter of 2006 respectively, and have steadily decreased from then on. Referrals of female patients were twice as common as male patient referrals. Patients in their sixth or seventh decade of life were most commonly referred, and more outpatients were referred compared to inpatients. 2. Patients with knee joint disorders were most commonly referred from the Western medical hospital to the Eastern medical hospital, followed by hip, shoulder, ankle, wrist, and elbow joint disorders. The most common disorders for each of the above regions in referred patients were knee osteoarthritis, avascular necrosis of the hip, adhesive capsulitis, and ankle strain and sprain. The generalized disorders rheumatoid arthritis and ankylosing spondylitis followed. 3. Patients referred to the Eastern hospital received approximately 3 to 10 Eastern medical treatment sessions. 45 percent remained on constant combination treatment, and 98 percent of referred patients received acupuncture treatment. Conclusions : In regard to the number of patients and duration of combination treatment, combination treatment was successfully performed for knee osteoarthritis, rheumatoid arthritis, and ankylosing spondylitis, while it was not so for avascular necrosis of the hip, adhesive capsulitis, and ankle strain and sprain. Further research on this subject is required.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.58 no.2
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• pp.196-202
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• 2013

This study was conducted to evaluate the performances of rice transgenic lines along with their wild types in terms of agronomic traits. A total of 32 rice transgenic lines, through previously conducted collaborative researches between molecular biologists and conventional rice breeders, were selected as promising lines. As the introduced functional genes, 17 genes, which were putatively related with high yield, disease and herbicide resistance, abiotic stress tolerance, and diversifying endosperm starch components, were transformed into three Japonica cultivars, Nipponbare, Nagdongbyeo, and Dongjinbyeo. The transgenic lines exhibited significantly deviated performances from their wild types on agronomic traits such as days to heading, culm length and yield potential. Multivariate analyses on transgenic lines to the evaluated agronomic traits also indicated random manner of phenotypic deviations from their wild type in terms of deviation directions and degrees. Our results suggested that, therefore, breeding strategies to control unexpected deleterious phenotypic performances among transgenic lines would be critical as much as the functions and proper expressions of the transformed genes.