• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.3
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• pp.221-232
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• 2023

In this paper, we propose a recommendation system based on the latent factor model using matrix factorization, which is one of the most commonly used collaborative filtering algorithms for recommendation systems. In particular, by introducing the concept of creating a list of recommended content and a list of non-preferred recommended content, and removing the non-preferred recommended content from the list of recommended content, we propose a method to ultimately increase the satisfaction. The experiment confirmed that using a separate list of non-preferred content to find non-preferred content increased precision by 135%, accuracy by 149%, and F1 score by 72% compared to using the existing recommendation list. In addition, assuming that users do not view non-preferred content through the proposed algorithm, the average evaluation score of a specific user used in the experiment increased by about 35%, from 2.55 to 3.44, thereby increasing user satisfaction. It has been confirmed that this algorithm is more effective than the algorithms used in existing recommendation systems.

• The Korean Journal of Applied Statistics
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• v.33 no.6
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• pp.833-842
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• 2020

Global platforms such as Netflix, Amazon, and YouTube have developed a precise recommendation system based on various information from large set of customers and many of the items recommended here are leading to actual purchases. In this paper, a cluster analysis was conducted according to the attribute of the content, expecting that there would be a difference in user preferences according to the attribute of the recommended content. Gower distance was used for use regardless of the type of variables. In this paper, using the data of movie rating site 'The Movie Dataset', the users were grouped hierarchically and recommended movies based on genre, director and actor variables. To evaluate the recommended systems proposed, user group was divided into train set and test set to examine the precision. The results showed that proposed algorithms have far higher precision than UBCF.

• Journal of Korean Society of Steel Construction
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• v.14 no.4
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• pp.549-556
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• 2002

The natural frequency of a system is commonly used in evaluating the serviceability condition of a floor. However. the current equations recommended in many building codes do not consider the various material types of a slab system; thus. different results are observed. Likewise. the transformation of a slab section required to predict the natural frequency of a composite deck plate is complicated. due to the varying shapes of the deck plates. Therefore. a new and simplified method of transforming a composite slab into an equivalent concrete slab is proposed. he modified vibration prediction equation was proposed based on the current vibration prediction equation recommended by LRFD. Compared to other equations. it is the closest to those obtained from experiments. The modified equation provides about 14.3% more accurate results than that recommended by LRFD. Likewise. the applicability of the proposed equation to other types of composite deck plate floor system was validated.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.29 no.1
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• pp.223-227
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• 2005

In adjacent sea areas of Yeosu, there are many crossing traffics between eastbound and westbound vessels. Traffic congestion is increasing in sea area of east Sori island and near Yokji Island. In this research, we established TSS near Yeokmando Areas and new recommended route which connected to Seopdo west recommended route to reduce meeting traffic between eastbound vessels and westbound vessels.

• The Journal of Korean Academic Society of Nursing Education
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• v.20 no.4
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• pp.596-605
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• 2014

Purpose: This study aims to understand the influence of college entrance system-related factors and scores of college scholastic ability test on a first year nursing student's academic achievement. Method: Data collected include both a descriptive survey designed to assess college entrance system-related factors with respect to 182 nursing students attending a 4-year nursing college program and their test scores in the first year. The data were analyzed via descriptive statistics, Mann-Whitney U test, Kruskal-Wallis test with Bonferroni's correction, and Spearman's rank correlation coefficient through an SPSS 18.0 program. Results: Student academic achievement with regard to college entrance system-related factors exhibited significant divergence from first year grade point averages (hereafter GPA) and natural science grades. Conclusion: This study confirmed the existence of significant differences, depending on the factors regarding the college entrance system. As a result, conducting assessment to evaluate the level of basic knowledge before college entrance is highly recommended. Also recommended is the development of a support program for students projected to have difficulties with respect to their academic achievement.

• Journal of Korea Multimedia Society
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• v.22 no.9
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• pp.1108-1121
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• 2019

As the quality and level of life rise, many people are doing search for various pieces of information about tourism. In addition, users prefer the search methods reflecting individual opinions such as SNS and blogs to the official websites of tourist destination. Many of previous studies focused on a recommendation system for tourist courses based on the GPS information and past travel records of users, but such a system was not capable of recommending the latest tourist trends. This study thus set out to collect and analyze the latest SNS data to recommend tourist destination of high interest among users. It also aimed to propose an altered TSP algorithm to recommend the optimal routes to the recommended destination within an area and a system to recommend the optimal tourist courses by applying the Elasticsearch engine. The altered TSP algorithm proposed in the study used the location information of users instead of Dijkstra's algorithm technique used in previous studies to select a certain tourist destination and allowed users to check the recommended courses for the entire tourist destination within an area, thus offering more diverse tourist destination recommendations than previous studies.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.61-65
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• 2000

This paper presents the load shedding case studies and recommendations of load shedding scheme For improving the reliability to suit the requirements of LG-Caltex refinery plant power sγstem. It is recommended for LG-Caltex to decrease the total generation for the economic dispatch. When the LG-Caltex refinery is isolated from KEPCO utility system, the proper load shedding scheme should be implemented since total generation in LG-Caltex refinery plant is less than the load demand. According to the studies carried out the logic-based load shedding is recommended as the main protection scheme, with the combination of the under-frequency relay load shedding.

• Journal of the Korea Safety Management & Science
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• v.16 no.1
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• pp.231-237
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• 2014

In order to improve participation and quick decision-making in an emergency, the Voluntary Participation Program was recommended in this study for effective management of Civil Defense. The problems in the Law and Administration group and Forced Education by Mobilization system were analyzed through actual conditions of Civil Defense management and participation. In order to improve these problems, cases such as "Extension of Participation Methods", "Cooperation Activities with Civil Groups", "Usage of Community Information" were studied. Based on the investigation results, domestic applicability was recommended.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.57 no.1
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• pp.69-77
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• 2021

The noise environment was evaluated using the ISO recommended NR evaluation curve and PSIL (Preferred Sound Interference Level) in order to investigate the onboard educational environment according to the noise in the Motor Vessel Saehaerim, a fishing training ship under making way. As a result, NRNs were measured at 37-61 dB in accommodation areas, 44-56 dB in work areas, 37-57 dB in educational and conference areas, 83-103 dB in engine areas and 65.3 dB and 51.2 dB in the work and education areas respectively based on PSIL. The NRNs, which evaluated the cabin of the experimental ship according to the purpose, exceeded all of the indoor standard noise recommended by the ISO, and the PSIL had a generally short conversational distance within 0.25-2.3 m and 0.75-1.3 m for teaching and work areas.

• Journal of Information Technology Services
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• v.20 no.4
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• pp.129-140
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• 2021

Recently, interest in AI tutors is rising as a way to bridge the educational gap in school settings. However, research confirming the effectiveness of AI tutors is lacking. The purpose of this study is to explore how effective learner characteristics and recommended item learning activities are in predicting learner's academic performance in an adaptive online learning environment. This study proposed the hypothesis that learner characteristics (prior knowledge, midterm evaluation) and recommended item learning activities (learning time, correct answer check, incorrect answer correction, satisfaction, correct answer rate) predict academic achievement. In order to verify the hypothesis, the data of 362 learners were analyzed by collecting data from the learning management system (LMS) from the perspective of learning analytics. For data analysis, regression analysis was performed using the regsubset function provided by the leaps package of the R program. The results of analyses showed that prior knowledge, midterm evaluation, correct answer confirmation, incorrect answer correction, and satisfaction had a positive effect on academic performance, but learning time had a negative effect on academic performance. On the other hand, the percentage of correct answers did not have a significant effect on academic performance. The results of this study suggest that recommended item learning activities, which mean behavioral indicators of interaction with AI tutors, are important in the learning process stage to increase academic performance in an adaptive online learning environment.