• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.12
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• pp.3266-3285
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• 2023

With the popularity of online learning, intelligent tutoring systems are starting to become mainstream for assisting online question practice. Surrounded by abundant learning resources, some students struggle to select the proper questions. Personalized question recommendation is crucial for supporting students in choosing the proper questions to improve their learning performance. However, traditional question recommendation methods (i.e., collaborative filtering (CF) and cognitive diagnosis model (CDM)) cannot meet students' needs well. The CDM-based question recommendation ignores students' requirements and similarities, resulting in inaccuracies in the recommendation. Even CF examines student similarities, it disregards their knowledge proficiency and struggles when generating questions of appropriate difficulty. To solve these issues, we first design an enhanced cognitive diagnosis process that integrates students' affection into traditional CDM by employing the non-compensatory bidimensional item response model (NCB-IRM) to enhance the representation of individual personality. Subsequently, we propose an affection-enhanced personalized question recommendation (AE-PQR) method for online learning. It introduces NCB-IRM to CF, considering both individual and common characteristics of students' responses to maintain rationality and accuracy for personalized question recommendation. Experimental results show that our proposed method improves the accuracy of diagnosed student cognition and the appropriateness of recommended questions.

• Asia pacific journal of information systems
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• v.30 no.4
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• pp.719-740
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• 2020

The stock market changes continuously as new information emerges, affecting the judgments of investors. Online news articles are valued as a traditional window to inform investors about various information that affects the stock market. This paper proposed new ways to utilize online news articles with technical indicators. The suggested hybrid model consists of three models. First, a self-attention-based convolutional neural network (CNN) model, considered to be better in interpreting the semantics of long texts, uses news content as inputs. Second, a self-attention-based, bi-long short-term memory (bi-LSTM) neural network model for short texts utilizes news titles as inputs. Third, a bi-LSTM model, considered to be better in analyzing context information and time-series models, uses 19 technical indicators as inputs. We used news articles from the previous day and technical indicators from the past seven days to predict the share price of the next day. An experiment was performed with Korean stock market data and news articles from 33 top companies over three years. Through this experiment, our proposed model showed better performance than previous approaches, which have mainly focused on news titles. This paper demonstrated that news titles and content should be treated in different ways for superior stock price prediction.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.330-333
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• 2005

In this study, a method of designing a neurointerface using neural network (NN) is proposed for controlling nonholonomic mobile robots. According to the concept of virtual master-slave robots, in particular, a partially stable inverse dynamic model of the master robot is acquired online through the NN by applying a feedback-error learning method, in which the feedback controller is assumed to be based on a PD compensator for such a nonholonomic robot. A tracking control problem is demonstrated by some simulations for a nonholonomic mobile robot with two-independent driving wheels.

• Asia pacific journal of information systems
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• v.25 no.2
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• pp.239-264
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• 2015

This study aims to investigate the effect of message content and source user identity on information diffusion in Twitter networks. For the empirical study, we collected 11,346 tweets pertaining to the three major mobile telecom carriers in Korea for three months, from September to December 2011. These tweets generated 59,111 retweets (RTs) and were retweeted at least once. Our analysis indicates that information diffusion in Twitter in terms of RT volume is affected primarily by the type of message content, such as the inclusion of corporate social responsibility activities. However, the effect of message content on information diffusion is heterogeneous to the identity of the information source. We argue that user identity affects recipients' perception of the credibility of focal information. Our study offers insights into the information diffusion mechanism in online social networks and provides managerial implications on the strategic utilization of online social networks for marketing communications with customers.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.69-72
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• 2002

본 논문에서 화자공간모델 evolution에 기반한 continuous density hidden Markov model (CDHMM)의 online 적응에 대한 새로운 기법을 제안한다. 학습화자의 a priori knowledge을 나타내는 화자공간모델은 factor analysis (FA) 또는 probabilistic principal component analysis (PPCA)와 같은 은닉변수모델(latent variable model)에 의해 효과적으로 나타내어진다. 은닉 변수모델은 화자공간모델뿐아니라 CDHMM 파라메터의 ajoint prior분포를 표시함으로, maximum a posteriori(MAP)적응기법에 직접 적용되어진다. 화자공간모델의 hyperparameters와 CDHMM파라메터를 동시에 순차적으로 적응하기 위해 quasi-Bayes (QB)추정 기술에 기반한 online 적응기법을 제안한다. 연속숫자음 인식과 관련된 화자적응 실험을 통해 제안된 기법은 적은 적응데이터에서 좋은 성능을 나타내며, 데이터가 증가함에 따라 성능이 지속적으로 증가함을 보여준다.

• Journal of The Korean Association For Science Education
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• v.24 no.6
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• pp.1206-1215
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• 2004

In this study, we explored the students' perceptions on the online discussion system for physics investigation as the physics education program. With these, we explored the characteristics of online discussion system. For these, the questions and interviews were executed in order to get informations about user-friendly characteristics of on-line discussion learning system of physics investigation, asynchronicity of on-line investigation discussion, on-line investigation discussion related to writing, visual cues and physical presence of on-line investigation discussion and preference of on-line investigation discussion. The students represented that there were two advantages in the online investigation discussion. One is that they could participate in the on-line investigation discussion without the restriction of time and space, and the other is that they could enter into a dispute with sufficient consideration because of the asynchronicity characteristic of online investigation discussion. Although the online educational activity is mainly achieved by independent work on the part of students, the role of teacher and parents is more important than the technical part of online educational system for the active participation.

• Journal of Korea Game Society
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• v.11 no.1
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• pp.69-78
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• 2011

2010, the China's online game industry has developed more than ten years. With the fast development of the China's online game industry, the china joy came into true in 2004. After 7 years of development China Joy has become Asia's largest exhibition game. The paper which from the china joy perspective compare and analyze the development process of china joy with the other two related exhibition E3 and TGS. The paper also select 6 important indicators to evaluate the china joy 1) the absolute number of the audiences from the show2) the number of the international visitors 3) the number of participating companies and corporate types4) the number of exhibitors and online game product quality5) the contents of the show 6) the international influence. From this perspective, the paper tries to figure out the status of the China's online game industry in the world online game industry. And after analysis 6 indicators we can make a conclusion of the international status of China joy and international influence. It also tries to find out the main problems in China's online game industry.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.3
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• pp.197-217
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• 2021

The purpose of this study is to analyze the utilization status of the Comprehensive Support System for Reading Education and other Online tools to draw implications for its improvement. The levels of utilization of the system before and after the COVID-19 were compared, in order to analyze the degree of support and the level of contribution of the system to school library education in the COVID-19 situation, where the online platform utilization has been maximized in elementary and secondary education. A questionnaire survey was conducted among teacher librarians to compare the perceptions of the overall online tools and the utilization of the system in the school library education before and after the COVID-19. Requirements for the better system primarily based on teacher librarians' opinions were analyzed. Based on these, it was possible to discover necessary implications for the improvement of the system in order for the system to function as an online platform for school libraries.

• Journal of Digital Convergence
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• v.19 no.8
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• pp.311-317
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• 2021

This study aims to propose an effective user experience of online class in the non-face-to-face through case analysis, focusing on school-linked education programs with art museums for elementary classes. To analysis domestic and international cases of school-liked education programs with art museum and to measure user experience, we were conducted with task test, in-depth interviews and surveys with experts. As a result, there were the pros and cons about the programs. Based on this, we propose a better method to increase the satisfaction of user experience for children. This study is significant in activating digital technology-based online education. This study expected to used as data on the user experience of a non-face-to-face online art education program in elementary schools in the future.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.8-12
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• 2023

With the recent expansion of online lectures, studies on their effectiveness and their influencing factors have increased. This study examines the factors affecting the satisfaction of online classes, considering the utilization and importance of online lectures, which have greatly increased in recent years. Based on the review of previous studies, this study identified learning presence, self-efficacy, and learning immersion as factors affecting the satisfaction of online classes, and suggested hypotheses that explain the relationship between these factors, and empirically reviewed the hypotheses. As a result of the study, it was found that learning presence and self-efficacy had a positive effect on learning immersion, and learning immersion had a positive effect on learning satisfaction. Based on the research results, some practical implications for improving the satisfaction of online classes were suggested.