• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.19-43
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• 2014

The Pareto principle, also known as the 80-20 rule, states that roughly 80% of the effects come from 20% of the causes for many events including natural phenomena. It has been recognized as a golden rule in business with a wide application of such discovery like 20 percent of customers resulting in 80 percent of total sales. On the other hand, the Long Tail theory, pointing out that "the trivial many" produces more value than "the vital few," has gained popularity in recent times with a tremendous reduction of distribution and inventory costs through the development of ICT(Information and Communication Technology). This study started with a view to illuminating how these two primary business paradigms-Pareto principle and Long Tail theory-relates to the success of virtual knowledge collaboration. The importance of virtual knowledge collaboration is soaring in this era of globalization and virtualization transcending geographical and temporal constraints. Many previous studies on knowledge sharing have focused on the factors to affect knowledge sharing, seeking to boost individual knowledge sharing and resolve the social dilemma caused from the fact that rational individuals are likely to rather consume than contribute knowledge. Knowledge collaboration can be defined as the creation of knowledge by not only sharing knowledge, but also by transforming and integrating such knowledge. In this perspective of knowledge collaboration, the relative distribution of knowledge sharing among participants can count as much as the absolute amounts of individual knowledge sharing. In particular, whether the more contribution of the upper 20 percent of participants in knowledge sharing will enhance the efficiency of overall knowledge collaboration is an issue of interest. This study deals with the effect of this sort of knowledge sharing distribution on the efficiency of knowledge collaboration and is extended to reflect the work characteristics. All analyses were conducted based on actual data instead of self-reported questionnaire surveys. More specifically, we analyzed the collaborative behaviors of editors of 2,978 English Wikipedia featured articles, which are the best quality grade of articles in English Wikipedia. We adopted Pareto ratio, the ratio of the number of knowledge contribution of the upper 20 percent of participants to the total number of knowledge contribution made by the total participants of an article group, to examine the effect of Pareto principle. In addition, Gini coefficient, which represents the inequality of income among a group of people, was applied to reveal the effect of inequality of knowledge contribution. Hypotheses were set up based on the assumption that the higher ratio of knowledge contribution by more highly motivated participants will lead to the higher collaboration efficiency, but if the ratio gets too high, the collaboration efficiency will be exacerbated because overall informational diversity is threatened and knowledge contribution of less motivated participants is intimidated. Cox regression models were formulated for each of the focal variables-Pareto ratio and Gini coefficient-with seven control variables such as the number of editors involved in an article, the average time length between successive edits of an article, the number of sections a featured article has, etc. The dependent variable of the Cox models is the time spent from article initiation to promotion to the featured article level, indicating the efficiency of knowledge collaboration. To examine whether the effects of the focal variables vary depending on the characteristics of a group task, we classified 2,978 featured articles into two categories: Academic and Non-academic. Academic articles refer to at least one paper published at an SCI, SSCI, A&HCI, or SCIE journal. We assumed that academic articles are more complex, entail more information processing and problem solving, and thus require more skill variety and expertise. The analysis results indicate the followings; First, Pareto ratio and inequality of knowledge sharing relates in a curvilinear fashion to the collaboration efficiency in an online community, promoting it to an optimal point and undermining it thereafter. Second, the curvilinear effect of Pareto ratio and inequality of knowledge sharing on the collaboration efficiency is more sensitive with a more academic task in an online community.

• Cartoon and Animation Studies
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• s.37
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• pp.393-411
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• 2014

The volume of world market for serious game in year 2015 is expected to be about 9.6 trillion, and the volume of educational serious game market is expected to surpass half of the whole serious game market. In Korea, the development of game for educational purpose has dominated around the education enterprises since late 90s. In 2008, 'Serious Game Forum' was founded led by the Ministry of Culture, Sports, and Tourism with experts from many fields in the society and there were progressing of making policies and plans for potential development of the serious game industry, but the effects were not successful than expected. In 2012, the Ministry of Education, Science, and Technology announced commercialization policy of digital textbook by 2015 and the serious game for educational purpose got attention again. Then, the serious game market became more vigorous with the dispersion of smart devices.13) As a result, the serious games on the smart devices or interlocking between the online and smart devices became an important issue in development rather than the online only serious games. Math field has international competitive power through export in the educational serious game market which takes more than half of the serious game market. Therefore, developing serious game for math education is a good area to raise competitiveness in domestic and international game industries. Moreover, it has no received preferences from students and parents although it has high potential for positive change of individuals and society. The reason is that students recognize it as educational content rather than a game and they avoid it, while parents recognize it as game but not an education. This phenomenon happens because the game elements and educational elements are not properly mixed but focused only on education or emphasized only the fun factors of game when it was developed. Therefore, the purpose of this research is to suggest a direction of developing serious games effectively combining with elementary math for elementary students to get interested in math while playing games. The research will analyze the current elementary math textbooks and find contents which may be combined with the game genre that elementary students enjoy playing these days. This research received advice from serious game developers and math education expert group to reflect the inclination of elementary school students, and respond to the demands from parents and educational institutions, and suggested a direction of developing serious games for effective math education.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.2
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• pp.61-73
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• 2021

This study aimed to identify the landscape perception and landscape characteristics of users by utilizing SNS data generated by their experiences. Therefore, how to recognize the main places and scenery appearing on the island, and what are the characteristics of the main scenery were analyzed using online text data and photo data. Text data are text mining and network structural analysis, while photographic data are landscape identification models and color analysis. As a result of the study, First, as a result of frequency analysis of Bakji·Banwol-do topics, we were able to derive keywords for local landscapes such as 'Purple Bridge', 'Doori Village', and location, behavior, and landscape images by analyzing them simultaneously. Second, the network structure analysis showed that the connection between key and undrawn keywords could be more specifically analyzed, indicating that creating landscapes using colors is affecting regional activation. Third, after analyzing the landscape identification model, it was found that artificial elements would be excluded to create preferred landscapes using the main targets of "Purple Bridge" and "Doori Village", and that it would be effective to set a view point of the sea and sky. Fourth, Bakji·Banwol-do were the first islands to be created under the theme of color, and the colors used in artificial facilities were similar to the surrounding environment, and were harmonized with contrasting lighting and saturation values. This study used online data uploaded directly by visitors in the landscape field to identify users' perceptions and objects of the landscape. Furthermore, the use of both text and photographic data to identify landscape recognition and characteristics is significant in that they can specifically identify which landscape and resources they prefer and perceive. In addition, the use of quantitative big data analysis and qualitative landscape identification models in identifying visitors' perceptions of local landscapes will help them understand the landscape more specifically through discussions based on results.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.4
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• pp.15-29
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• 2021

The study aims to grasp the perception and appraisal of urban park users through text analysis. This study used Google review data provided by Google Maps. Google Maps Review is an online review platform that provides information evaluating locations through social media and provides an understanding of locations from the perspective of general reviewers and regional guides who are registered as members of Google Maps. The study determined if the Google Maps Reviews were useful for extracting meaningful information about the user perceptions and appraisals for parks management plans. The study chose three urban parks in Seoul, South Korea; Seoul Forest, Boramae Park, and Olympic Park. Review data for each of these three parks were collected via web crawling using Python. Through text analysis, the keywords and network structure characteristics for each park were analyzed. The text was analyzed, as were park ratings, and the analysis compared the reviews of residents and foreign tourists. The common keywords found in the review comments for the three parks were "walking", "bicycle", "rest" and "picnic" for activities, "family", "child" and "dogs" for accompanying types, and "playground" and "walking trail" for park facilities. Looking at the characteristics of each park, Seoul Forest shows many outdoor activities based on nature, while the lack of parking spaces and congestion on weekends negatively impacted users. Boramae Park has the appearance of a city park, with various facilities providing numerous activities, but reviewers often cited the park's complexity and the negative aspects in terms of dog walking groups. At Olympic Park, large-scale complex facilities and cultural events were frequently mentioned, emphasizing its entertainment functions. Google Maps Review can function as useful data to identify parks' overall users' experiences and general feelings. Compared to data from other social media sites, Google Maps Review's data provides ratings and understanding factors, including user satisfaction and dissatisfaction.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.1-15
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• 2021

If it is difficult for us to make decisions, we ask for advice from friends or people around us. When we decide to buy products online, we read anonymous reviews and buy them. With the advent of the Data-driven era, IT technology's development is spilling out many data from individuals to objects. Companies or individuals have accumulated, processed, and analyzed such a large amount of data that they can now make decisions or execute directly using data that used to depend on experts. Nowadays, the recommender system plays a vital role in determining the user's preferences to purchase goods and uses a recommender system to induce clicks on web services (Facebook, Amazon, Netflix, Youtube). For example, Youtube's recommender system, which is used by 1 billion people worldwide every month, includes videos that users like, "like" and videos they watched. Recommended system research is deeply linked to practical business. Therefore, many researchers are interested in building better solutions. Recommender systems use the information obtained from their users to generate recommendations because the development of the provided recommender systems requires information on items that are likely to be preferred by the user. We began to trust patterns and rules derived from data rather than empirical intuition through the recommender systems. The capacity and development of data have led machine learning to develop deep learning. However, such recommender systems are not all solutions. Proceeding with the recommender systems, there should be no scarcity in all data and a sufficient amount. Also, it requires detailed information about the individual. The recommender systems work correctly when these conditions operate. The recommender systems become a complex problem for both consumers and sellers when the interaction log is insufficient. Because the seller's perspective needs to make recommendations at a personal level to the consumer and receive appropriate recommendations with reliable data from the consumer's perspective. In this paper, to improve the accuracy problem for "appropriate recommendation" to consumers, the recommender systems are proposed in combination with context-based deep learning. This research is to combine user-based data to create hybrid Recommender Systems. The hybrid approach developed is not a collaborative type of Recommender Systems, but a collaborative extension that integrates user data with deep learning. Customer review data were used for the data set. Consumers buy products in online shopping malls and then evaluate product reviews. Rating reviews are based on reviews from buyers who have already purchased, giving users confidence before purchasing the product. However, the recommendation system mainly uses scores or ratings rather than reviews to suggest items purchased by many users. In fact, consumer reviews include product opinions and user sentiment that will be spent on evaluation. By incorporating these parts into the study, this paper aims to improve the recommendation system. This study is an algorithm used when individuals have difficulty in selecting an item. Consumer reviews and record patterns made it possible to rely on recommendations appropriately. The algorithm implements a recommendation system through collaborative filtering. This study's predictive accuracy is measured by Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). Netflix is strategically using the referral system in its programs through competitions that reduce RMSE every year, making fair use of predictive accuracy. Research on hybrid recommender systems combining the NLP approach for personalization recommender systems, deep learning base, etc. has been increasing. Among NLP studies, sentiment analysis began to take shape in the mid-2000s as user review data increased. Sentiment analysis is a text classification task based on machine learning. The machine learning-based sentiment analysis has a disadvantage in that it is difficult to identify the review's information expression because it is challenging to consider the text's characteristics. In this study, we propose a deep learning recommender system that utilizes BERT's sentiment analysis by minimizing the disadvantages of machine learning. This study offers a deep learning recommender system that uses BERT's sentiment analysis by reducing the disadvantages of machine learning. The comparison model was performed through a recommender system based on Naive-CF(collaborative filtering), SVD(singular value decomposition)-CF, MF(matrix factorization)-CF, BPR-MF(Bayesian personalized ranking matrix factorization)-CF, LSTM, CNN-LSTM, GRU(Gated Recurrent Units). As a result of the experiment, the recommender system based on BERT was the best.

• The Journal of KAIRB
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• v.2 no.2
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• pp.37-48
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• 2020

Purpose: The purpose of this study is to assess the operational status and level of understanding among IRB and HRPP staffs at a hospital or a research institute to the HRPP guideline set by the Ministry of Food and Drug Safety (MFDS) and to provide recommendations. Methods: Online survey was distributed among members of Korean Association of IRB (KAIRB) through each IRB office. The result was separated according to topic and descriptive statistics was used for analysis. Result: Survey notification was sent out to 176 institutions and 65 (37.1%) institutions answered the survey by online. Of 65 institutions that answered the survey; 83.1% was hospital, 12.3% was university, 3.1% was medical college, 1.5% was research institution. 23 institutions (25.4%) established independent HRPP offices and 39 institutions (60.0%) did not. 12 institutions (18.5%) had separate IRB and HRPP heads, 21 (32.3%) institutions separated business reporting procedure and person in charge, 12 institutions separated the responsibility of IRB and HRPP among staff, and 45 institutions (69.2%) had audit & non-compliance managers. When asked about the most important basic task for HRPP, 23% answered self-audit. And according to 43.52%, self-audit was also the most by both institutions that operated HRPP and institutions that did not. When basic task performance status was analyzed, on average, the institutions that operated HRPP was 14% higher than institutions that only operated IRB. 9 (13.8%) institutions were evaluated and obtained HRPP accreditation from MFDS and the most common reason for obtaining the accreditation was to be selected as Institution for the education of persons conducting clinical trial (6 institutions). The most common reason for not obtaining HRPP accreditation was because of insufficient staff and limited capacity of the institution (28%). Institutions with and without a plan to be HRPP accredited by MFDS were 20 (37.7%) each. 34 institutions (52.3%) answered HRPP evaluation method and accreditation by MFDS was appropriate while 31 institutions (47.7%) answered otherwise. 36 institutions answered that HRPP evaluation and accreditation by MFDS was credible while 29 institutions (44.5%) answered that HRPP evaluation method and accreditation by MFDS was not credible. Conclusion: 1. MFDS's HRPP accreditation program can facilitate the main objective of HRPP and MFDS's HRPP accreditation program should be encouraged to non-tertiary hospitals by taking small staff size into consideration and issuing accreditation by segregating accreditation. 2. While issuing Institution for the education of persons conducting clinical trial status as a benefit of MFDS's HRPP accreditation program, it can also hinder access to MFDS's HRPP accreditation program. It should also be considered that the non-contact culture during COVID-19 pandemic eliminated time and space limitation for education. 3. For clinical research conducted internally by an institution, internal audit is the most effective and sole method of protecting safety and right of the test subjects and integrity for research in Korea. For this reason, regardless of the size of the institution, an internal audit should be enforced. 4. It is necessary for KAIRB and MFDSto improve HRPP awareness by advocating and educating the concept and necessity of HRPP in clinical research. 5. A new HRPP accreditation system should be setup for all clinical research with human subjects, including Investigational New Drug (IND) application in near future.

• Journal of Nutrition and Health
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• v.51 no.5
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• pp.433-444
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• 2018

Purpose: This study examined the status and needs of school-based nutritional education programs for reducing sugars intake in elementary schools. Methods: A total of 230 elementary nutrition teachers participated in this study through an online survey in July 2017. Results: Approximately one-third of the schools conducted nutrition education on reducing sugars intake as a main topic. The most frequent educated grade and education period were $4^{th}$ and $3^{rd}$ grade, and once a year. Most of the nutrition teachers answered that nutrition education related to reducing sugars intake for children was necessary. The nutrition teachers answered that first graders were the recipients in most need of nutrition education for reducing sugars but, realistically, third graders were the most suitable for nutrition education. The appropriate education topics were limited to the lower grades, such as sugars consumption related health problems, foods containing high sugars, and behaviors to reduce sugars intake; however, a wider variety of topics were selected for the upper grades. The experiment was considered to be an effective educational method for both the lower and upper grades. The most appropriate nutrition education media appeared to be a mock-up in the lower grades, and an experiment kit in the upper grades. Games and videos were highly considered to be effective media to educate students in reducing sugars consumption by voluntary participation in free time in the classroom in both the lower and upper grades. Conclusion: Nutrition education programs focusing on sugars intake reduction were conducted in some elementary schools, but the training time was short and the types of activities were limited. The perception and demand for nutrition education was very high. Therefore, the development and dissemination of elementary school-based nutritional education programs for sugars intake reduction is urgently needed. Moreover, to develop an effective nutrition education program, the education environment and demand in the field should be fully considered.

• Archives of design research
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• v.20 no.3 s.71
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• pp.315-324
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• 2007

The fast development of the information technology makes Korea one of the most advanced countries in information communication in the world in a short period of time. However, the gap between the aged and the young has been seriously increased. Those who are less than 10% of the older adults are using the internet at present. It means the elderly has many difficulties in using the internet because of their physical and cognitive differences. The purpose of this study is that the aged can easily achieve and use information by developing a guidelines for the Korean typography in the web interface. A literature search was conducted on the web interface design guidelines for older adults. These guidelines were classified by interface component and the study subjects needed for the Korean internet environment were selected. The subjects are a more comfortably readable typeface according to the sizes, a proper text size of Gulim and Batang, a more comfortably readable leading size, the appropriate letter spacing, the proper line length of body, the suitable size proportion between a title and a body, and a more comfortably readable text alignment. Survey questions were made and these Questions were improved after the pretest. Both online and offline survey programs were written and the aged and the young were tested with these programs. The result of this survey shows that there are satisfaction differences between the aged and the young in the readability and legibility of the web contents. Therefore these universal guidelines to be used in the Korean typographical environment for the future aged population were specified. It is expected that this study will be used as basic data for the universal web interface where the older adults can easily use and acquire information.

• Journal of the Korean Society of Earth Science Education
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• v.10 no.3
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• pp.262-277
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• 2017

Digital textbooks enable learning that is appropriate to the characteristics and level of learners through various interactions. The purpose of this study was to develop an instruction model that can more effectively use digital textbooks in elementary science classes and to verify its effectiveness. The results were as follows. The instruction model for helping learners complete their learning by using digital textbooks needs to receive diagnostic assessment and feedback on entry behavior, to build a self-directed learning environment, and to interact with teachers, students, and digital textbooks as scaffolding. In this study, we developed an instruction model using digital textbooks reflecting these characteristic. The instructional model consists of preparation, practice and solidity step. In the preparation step, the learner performs a diagnostic evaluation using digital textbooks. Based on the results, feedback provided at each level can complement the entry behavior and maintain interest in learning activities. In the practice step, self-directed learning is implemented using diverse functions of digital textbooks and various types of data. In the solidity step, learners can internalize the learning contents by reviewing video clips which are provided by teachers, performing problem-solving activities, and accessing outcomes accumulated by learners in the community online. In order to verify the effectiveness of this model, we selected the "Weather and our Life" unit. This experiment was conducted using 101 students in the 5th grade in B Elementary School in Gwangju Metropolitan City. In the experimental group, 50 students learned using a smart device that embodies digital textbooks applied with the instruction model. In the comparative group, 51 students were taught using the paper textbooks. The results were as follows. First, there was a significant effect on the improvement of the learning achievement in the experimental group with low academic ability compared with the comparative group with low academic ability. Second, there was a significant effect on self-directed learning attitude in the experimental group. Third, in the experimental group, the number of interactions with the learner, teacher, and digital textbook was higher than the comparative group. In conclusion, the digital textbooks based on the instruction model in elementary science classes developed in this study helped to improve learners' learning achievement and self-directed learning attitudes.

• Journal of The Korean Association For Science Education
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• v.37 no.2
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• pp.359-370
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• 2017

The purpose of this study is to explore the changes caused by using smart technology in school science inquiry. For this, we investigated 12 elementary school teachers' perceptions by using an open-ended questionnaire, group discussions, classroom discussions, and participant interviews. The results of this study indicate that the introduction of technology into classroom inquiry can open up the various possibilities and can cause additional burdens as well. First, teachers explained that smart technology can expand the opportunities to observe natural phenomena such as constellations and changing phases of the moon. However, some teachers insisted that, sometimes, learning how to use new devices disrupts students' concentration on the inquiry process itself. Second, teachers introduced the way of digital measurement using smart phone sensors in inquiry activities. They said that digital measurement is useful in terms of the reduction of errors and of the simplicity to measure. However, other teachers insisted that using new devices in classroom inquiry can entail additional variables and confuse the students' focus of inquiry. Communication about inquiry process can also be improved by using digital media. However, some teachers emphasized that they always talked about both the purpose of using SNS and online etiquettes with their students before using SNS. Based on these results, we discussed the necessity of additional analysis on the various ways of using digital devices depending on teachers' perceptions, the types of digital competency required in science inquiry using smart technology, and the features of norms shaped in inquiry activities using smart technology.