• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.105-110
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• 2003

Collaborative filtering is one of the methodologies that are most widely used for recommendation system. It is based on a data matrix of each customer's preferences of products. There could be a lot of missing values in such preference. data matrix. This incomplete data is one of the reasons to deteriorate the accuracy of recommendation system. Multiple imputation method imputes m values for each missing value. It overcomes flaws of single imputation approaches through considering the uncertainty of missing values.. The objective of this paper is to suggest multiple imputation-based collaborative filtering approach for recommendation system to improve the accuracy in prediction performance. The experimental works show that the proposed approach provides better performance than the traditional Collaborative filtering approach, especially in case that there are a lot of missing values in dataset used for recommendation system.

• The Journal of Industrial Distribution & Business
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• v.12 no.5
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• pp.27-36
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• 2021

Purpose: This study empirically investigates the effect of collaborative communication and information sharing on the supply chain performance of South Korean pharmaceutical companies. Specifically, it understands the importance collaborative communication and suggests a method for investigating communication in academic research on the pharmaceutical industry. Investigating this sector is crucial because the importance of the pharmaceutical industry is increasing globally against the background of the Covid-19 pandemic. Research design, data, and methodology: A questionnaire was administered to employees of South Korean pharmaceutical companies and 244 valid responses were used for the statistical analysis. Additionally, structural equation modeling was used to measure the relationships between the observed and latent variables. Results: Collaborative communication has a positive effect on information sharing. However, information sharing, unlike collaborative communication, does not exhibit a significant positive relationship with supply chain performance. These results indicate that it is important to communicate effectively in the supply chain rather than strive for the right type of information sharing. Conclusions: Consumers and retailers within the supply chain should continue to strive for candid communication. This study is meaningful, as it empirically tests the relationships between collaborative communication, information sharing, and supply chain performance in the South Korean pharmaceutical industry.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.3
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• pp.105-115
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• 2023

This study analyzed the effects of learning participation motivation and collaborative self-efficacy on knowledge sharing behavior in an online learning environment. Collaborative learning in the online learning environment took the initiative in team formation, learning topic selection, learning planning and execution, and reflection. Collaborative learning was operated as an extracurricular program, and a survey was conducted targeting students who finally completed all learning activities. The results of the study are as follows. First, goal-oriented motivation and self-Efficacy for group work, showed significant influence on knowledge sharing behavior. Second, activity-oriented motivation did not show a statistically significant effect relationship. Interpreting the analysis results, it can be judged that the higher the goal-oriented motivation and self-Efficacy for group work of students who performed collaborative learning in an online learning environment, the higher the willingness to share knowledge, skills, and information they know. This study explored the outcomes of collaborative learning conducted in an online learning environment. It is meaningful that the learner's learning participation motivation was identified and the effect of self-Efficacy for group work, which can be expressed in collaborative learning situations, on knowledge sharing behavior, which is a necessary behavior for group performance, is significant.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.14-15
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• 2007

Now-a-days, data and task migration in collaborative work provides enormous facilities to users. Here, we propose an ontology-based information management scheme to facilitate data and task migration in collaborative work. This ontologybased model will help us to organize huge information (e.g. device status, runtime state etc.) efficiently.

• The Journal of Industrial Distribution & Business
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• v.10 no.2
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• pp.25-37
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• 2019

Purpose - The goal of this study is to analyze the differences in education performances between students of the government's financial support program and those who do not receive support at a local university in Korea. Research design, data, and methodology - The questionnaire used was NASEL. NASEL is considered a highly suitable survey tool for professors, courses, and performances in Korean universities. The 290 students who participated and 44 students do not participate in the financial support program were surveyed for 10 days. The characteristics of students were investigated by frequency analysis and technical statistics. The analysis of student collective characteristics used independent t and f-tests,and one-way ANOVA with IBM SPSS Statistics 22.0 for statistical purposes. Results - The p-value of the group receiving financial support and the group without financial support in active-collaborative learning is 0.167. The p-value of the economically supported group and the non-supported group of the faculty-student interaction is 0.281. The confidence coefficient of the active-collaborative learning questionnaire is 0.861. The reliability coefficient of the questionnaire for the faculty-student interaction questionnaire is 0.871. Conclusions - There are no clear differences in active-collaborative learning and faculty-student interaction between participating and non-participating students in the economic program.

• The Journal of Korean Association of Computer Education
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• v.10 no.2
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• pp.115-123
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• 2007

Collaborative knowledge is continuously producted and modified by group individuals during collaboration and it is also fostered in a radical trust environment like Wiki. The example is Wikipedia. However I found out a big problem as difficulties of exploring when the knowledge space is extended more and more widely. To solve this problem, collaborative knowledge management systems are implemented based on wiki. The one is navigation map that supports the efficient exploring and the another is knowledge map that supports a convergent thinking in a group. In this study, we examined the effectiveness of navigation map and knowledge map.

• Journal of Engineering Education Research
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• v.25 no.1
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• pp.46-54
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• 2022

This study attempted non-face-to-face collaborative product development practice that can respond to the spread of COVID-19 by expanding existing product data management system-based product development practice. For the complete non-face-to-face product development practice, it utilized prototype development using a 3D paper model, an online class management system and social media for classes and meetings. As a result of applying the non-face-to-face method, product developments of 26 practice teams have been completed without any failures. Therefore, through this study, the author can confirm that it is possible to provide the complete non-face-to-face collaborative product development practice based on product data management systems.

• Asia pacific journal of information systems
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• v.27 no.2
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• pp.126-138
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• 2017

The proliferation of items increased the difficulty of customers in finding the specific items they want to purchase. To solve this problem, companies adopted recommender systems, such as collaborative filtering systems, to provide personalization services. However, companies use only meaningful and essential data given the explosive growth of data. Some customers are concerned that their private information may be exposed because CF systems necessarily deal with personal information. Based on these concerns, we analyze the effects of the amount of information on recommendation performance. We assume that a customer could choose to provide overall information or partial information. Experimental results indicate that customers who provided overall information generally demonstrated high performance, but differences exist according to the characteristics of products. Our study can provide companies with insights concerning the efficient utilization of data.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.9
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• pp.27-31
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• 2003

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.06a
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• pp.1063-1064
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• 2009