• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.11
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• pp.2866-2879
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• 2012

Among the various security threats in online games, the use of game bots is the most serious problem. Previous studies on game bot detection have proposed many methods to find out discriminable behaviors of bots from humans based on the fact that a bot's playing pattern is different from that of a human. In this paper, we look at the chatting data that reflects gamers' communication patterns and propose a communication pattern analysis framework for online game bot detection. In massive multi-user online role playing games (MMORPGs), game bots use chatting message in a different way from normal users. We derive four features; a network feature, a descriptive feature, a diversity feature and a text feature. To measure the diversity of communication patterns, we propose lightly summarized indices, which are computationally inexpensive and intuitive. For text features, we derive lexical, syntactic and semantic features from chatting contents using text mining techniques. To build the learning model for game bot detection, we test and compare three classification models: the random forest, logistic regression and lazy learning. We apply the proposed framework to AION operated by NCsoft, a leading online game company in Korea. As a result of our experiments, we found that the random forest outperforms the logistic regression and lazy learning. The model that employs the entire feature sets gives the highest performance with a precision value of 0.893 and a recall value of 0.965.

• Journal of Engineering Education Research
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• v.5 no.2
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• pp.10-21
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• 2002

In the knowledge based society, the development of creative human resources is one of the core factors for securing a national competition power. Especially in the software industries, the development of human resources who can solve a problem creatively by applying object oriented programming technique which is a update Programming technology is required. In this paper, we designed a lecture plan and produced it into a course contents which could be run on a online learning system. The teaching focuses of the developed course are the development of problem solving ability and object oriented design and programming ability through Java.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.16-30
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• 2023

The elderly population is increasing owing to a low fertility rate and an aging population. In addition, life expectancy is increasing, and the advancement of medicine has increased the importance of health to most people. Therefore, government and companies are developing and supporting smart healthcare, which is a health-related product or industry, and providing related services. Moreover, with the development of the Internet, many people are managing their health through online searches. The most convenient way to achieve such management is by consuming nutritional supplements or seasonal foods to prevent a nutrient deficiency. However, before implementing such methods, knowing the nutrient status of the individual is difficult, and even if a test method is developed, the cost of the test will be a burden. To solve this problem, we developed a questionnaire related to nutrient classification twice, based upon which an adaptive algorithm was designed. This algorithm was designed as a machine learning based algorithm for nutrient classification and its accuracy was much better than the other machine learning algorithm.

• The Journal of the Korea Contents Association
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• v.8 no.12
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• pp.457-464
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• 2008

This study is to design, develope, and deploy of e-learning inquiry based content in elementary science class. First, this study analyzed related literature review, case studies, and inquiry based class models for seeking better applicable design and development modes. From focus group meeting, experts discussed the inquiry content design ideas for elementary students for science class. This study finally established its own inquiry design mode for online science class with the flow of understanding of problem, sep up hypothesis, problem solving, and solution analysis. The developed content was deployed in real classroom setting to see how students received the contents and how well they processed the learning activities. We found that inquiry based online content, especially when applied to science subject, can be effective in students interests and their motivations. We also observed that there were a few managerial errors such as detailed lesson guidance and tutor support for students activities. This study concluded that inquiry based online contents should be designed considering students interests based on learning subjects and also developed in terms of students interests and strong motivation as well. We suggest that related research should be expanded toward to other subject than science and various students age groups.

• Journal of Platform Technology
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• v.11 no.3
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• pp.45-55
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• 2023

This paper presents a model that supports decision-makers in the Korean film industry to maximize the success of online movies. To achieve this, we collected historical box office movies and clustered them into types to propose a model predicting each type's online box office performance. We considered various features to identify factors contributing to movie success and reduced feature dimensionality for computational efficiency. We systematically classified the movies into types and predicted each type's online box office performance while analyzing the contributing factors. We used automated machine learning (AutoML) techniques to automatically propose and select machine learning algorithms optimized for the problem, allowing for easy experimentation and selection of multiple algorithms. This approach is expected to provide a foundation for informed decision-making and contribute to better performance in the film industry.

• Language and Information
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• v.14 no.2
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• pp.159-181
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• 2010

This paper presents a hybrid approach to the sentiment analysis of online texts. The sentiment of a text refers to the feelings that the author of a text has towards a certain topic. Many existing approaches employ either a pattern-based approach or a machine learning based approach. The former shows relatively high precision in classifying the sentiments, but suffers from the data sparseness problem, i.e. the lack of patterns. The latter approach shows relatively lower precision, but 100% recall. The approach presented in the current work adopts the merits of both approaches. It combines the pattern-based approach with the machine learning based approach, so that the relatively high precision and high recall can be maintained. Our experiment shows that the hybrid approach improves the F-measure score for more than 50% in comparison with the pattern-based approach and for around 1% comparing with the machine learning based approach. The numerical improvement from the machine learning based approach might not seem to be quite encouraging, but the fact that in the current approach not only the sentiment or the polarity information of sentences but also the additional information such as target of sentiments can be classified makes the current approach promising.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.211-221
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• 2023

After COVID-19, various metaverse platforms for online lectures are being provided. Most of the classrooms are tiered type, and they are divided into intensive classrooms and open classrooms depending on the shape of the classrooms. Intensive classrooms provide a one-sided lecture format, so there are many difficulties in conducting communication-based classes that carry out team missions like PBL classes. In this study, we propose a metaverse classroom that applies the functions of a multiplayer online role-playing game (MMORPG), one of the game genres suitable for PBL classes. The proposed system provides various interaction techniques for PBL classes. We evaluated user satisfaction when this was applied to actual classes. As a result of the evaluation, it was found that users preferred text and voice chatting more than video chatting and solving missions like games was very helpful in online classes.

• Journal of The Korean Association of Information Education
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• v.12 no.2
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• pp.223-234
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• 2008

Educating qualified elementary school teachers depends on excellent pre-service education. The high quality of education is accomplished by various interactions between teachers and learners, as well as active participation by students. In the present study, online problem-based learning and an e-portfolio were used to examine the effect on the computer-curriculum education to reflect social and individual needs, and to enhance the quality of instruction at universities. Students (n=105) participated in six different problem-based learning sessions. At the same time, they developed Blog e-portfolios as individual and group products, and wrote reflective journals that focused on their learning processes and results. A qualitative analysis method was employed to analyze the reflective journals. The results of the analyses showed the following: 1) Increasing the understanding of the computer-curriculum education, 2) enhancing students' competence in using ICT potentially, 3) cultivating student-centered teaching and learning strategies on ICT, and 4) enhancing competence of future teaching activities through experiencing e-portfolio as a performance-assessment tool.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.347-364
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• 2022

Fraudulent companies or sellers strategically manipulate reviews to influence customers' purchase decisions; therefore, the reliability of reviews has become crucial for customer decision-making. Since customers increasingly rely on online reviews to search for more detailed information about products or services before purchasing, many researchers focus on detecting manipulated reviews. However, the main problem in detecting manipulated reviews is the difficulties with obtaining data with manipulated reviews to utilize machine learning techniques with sufficient data. Also, the number of manipulated reviews is insufficient compared with the number of non-manipulated reviews, so the class imbalance problem occurs. The class with fewer examples is under-represented and can hamper a model's accuracy, so machine learning methods suffer from the class imbalance problem and solving the class imbalance problem is important to build an accurate model for detecting manipulated reviews. Thus, we propose an OpenAI-based reviews generation model to solve the manipulated reviews imbalance problem, thereby enhancing the accuracy of manipulated reviews detection. In this research, we applied the novel autoregressive language model - GPT-3 to generate reviews based on manipulated reviews. Moreover, we found that applying GPT-3 model for oversampling manipulated reviews can recover a satisfactory portion of performance losses and shows better performance in classification (logit, decision tree, neural networks) than traditional oversampling models such as random oversampling and SMOTE.

• Journal of Engineering Education Research
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• v.19 no.1
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• pp.37-46
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• 2016

The purposes of the study were to examine engineering students' concerns and problems while they were choosing a project topic in interdisciplinary collaboration and to suggest ways to support them in an early stage of collaboration phase. To answer the research questions, we conducted a case study with engineering participants in GCTI 2015, an interdisciplinary collaborative and creative group project. Multiple data sources including focus group interviews, online survey and researchers' observation notes were used to triangulate research findings. We found four main concerns of engineering students. These concerns include (1) lack of self-efficacy, (2) limited resources, (3) lack of shared, meaningful, and common goals, and (4) lack of content knowledge. Based on these concerns we proposed four supports in an early stage of the collaborative project. These supports includes (1) implementing an orientation program, (2) providing opportunities for social interactions, (3) providing expert feedback, and (4) providing consultation for team building.