• Proceedings of the Korean Information Science Society Conference
• /
• 2001.10b
• /
• pp.148-150
• /
• 2001

발견된 Web Usage 패턴들은 분석하는 전문가에게는 불필요하고 흥미롭지 못해 의사결정에 도움이 못되는 경우가 많다. 따라서 발견된 패턴에 대한 도메인 전문가의 사전 Belief에 기반한 패턴 검증 과정이 필요하다. 발견된 패턴의 유용성 여부는 패턴의 Unexpectedness를 측정함으로써 결정할 수 있다. 본 논문에서는 패턴의 Unexpectedness를 전문가의 Belief에 기반하여 검증하기 위한 새로운 방법론 제안한다. 발견된 패턴과 전문가 Belief를 매칭 알고리즘을 이용하여 패턴을 4가지(완전일치, 조건부 일치, 결과부 일치, 완전 불일치)로 분류하는 1차 검증과 1차 검증 결과의 4가지 분류데이터를 통계적 추론 방법인 Dempster-chafer에 적용한 2차 검증으로 나뉜다. 1차 검증 과정은 패턴의 분류 용이성을 부여하나 패턴의 Unexpectedness에 대한 신뢰성을 제공하지 못한다. 이 문제점을 2차 검증 과정을 통해 해결한다.

• Educational Technology International
• /
• v.21 no.1
• /
• pp.97-123
• /
• 2020

The purpose of this study is to investigate the emotions of students toward using digital textbooks, and to examine the factors affecting the emotions. This study examined the relationship between individual characteristics and computer usage, students' emotions, and the perceived learning effects. For this study, 2,950 1st grade middle school students participated in a survey which measured individual characteristics, computer usage behavior, emotions toward using digital textbooks, and perceived learning effects of digital textbooks. The results showed that positive emotions toward using digital textbooks were higher than negative emotions. The students' positive emotions were most affected by intrinsic motivation, self-regulated learning, and student's use of computers for learning and entertainment. Similarly, perceived learning effects were positively correlated to intrinsic motivation and self-regulated learning, but the students' positive emotions towards using digital textbooks was the strongest predictor. Digital textbook efficacy was the most influential factor that affected the students' negative emotions, while computer addiction was associated with negative emotions.

• Journal of Computing Science and Engineering
• /
• v.5 no.4
• /
• pp.338-345
• /
• 2011

Nowadays mobile devices are used for various applications such as making voice/video calls, browsing the Internet, listening to music etc. The average battery consumption of each of these activities and the length of time a user spends on each one determines the battery lifetime of a mobile device. Previous methods have provided predictions of battery lifetime using a static battery consumption rate that does not consider user characteristics. This paper proposes an approach to predict a mobile device's available battery lifetime based on usage patterns. Because every user has a different pattern of voice calls, data communication, and video call usage, we can use such usage patterns for personalized prediction of battery lifetime. Firstly, we define one or more states that affect battery consumption. Then, we record time-series log data related to battery consumption and the use time of each state. We calculate the average battery consumption rate for each state and determine the usage pattern based on the time-series data. Finally, we predict the available battery time based on the average battery consumption rate for each state and the usage pattern. We also present the experimental trials used to validate our approach in the real world.

• Journal of the Korea Society of Computer and Information
• /
• v.20 no.7
• /
• pp.77-84
• /
• 2015

The study is to investigate which features are perceived by Social Network Service(SNS) users as the most required one to further boost the usage of service, and to examine the perception of these features of SNS sites varies according to their demographic and service usage characteristics. The study also is to suggest a few of research propositions on the relationships between required features of SNS sites and characteristics of SNS users, based on statistical analyses. To accomplish these research purposes, the study defined characteristics of SNS users including demographic(gender, age) and service usage one(start time of service usage, service usage place), and required features of SNS sites(system, service, information, emotion) based on the literature review of SNS. The results show, based on the statistical analyses using survey questionnaire on Korean and Chinese SNS users, that there are differences in perception of required features of SNS sites among the respondents grouped by age, start time of service usage, service usage place. Finally, the study proposed three research propositions, based on the analysis result, that could be used in SNS related researches in the future.

• Proceedings of the KIEE Conference
• /
• 2000.11d
• /
• pp.827-829
• /
• 2000

오늘날 인터넷 사용자들은 정보의 홍수 속에 놓여있다. 웹사이트에 들어가면 대부분은 자신과 관련 없는 정보들이 쏟아진다. 따라서 인터넷 사용자들의 관심에 맞는 내용을 제 공해주어 시간의 절약과 동시에 사용자에게 가치 있는 정보를 제공할 수 있게 하는 서비스가 필요하다. 이러한 개인화 된 서비스를 제공해주기 위해 사용자에 대한 정확한 분석을 바탕으로 사용자에게 효율적인 서비스를 제공하여야 할 것이다. 따라서 본 논문에서는 사용자 프로파일 및 웹 로그 등을 토대로 각 고객의 성향과 패턴을 정확하게 분석하여, 사용자 각 개인에게 적합하며 효율적인 서비스를 제공해 줄 수 있는 Web Usage Mining 을 통한 사용자 패턴 추출 알고리즘을 개발하고자 한다. 본 논문에서 연구한 Web Usage Mining 알고리즘은 사용자의 웹 사용 습관을 토대로 데이터 마이닝의 과정을 거쳐 사용자의 성향과 관심을 결정하고, 이를 바탕으로 사용자에게 알맞은 내용을 제공할 수 있도록 할 것이다. 이때, 사용자의 정보는 웹 내에서의 행동 중에서 중요하게 사용되는 특정한 페이지를 보는 시간, 웹 서핑 패턴, 전자 상거래 사이트의 경우에는 구매한 상품과 쇼핑 카트에 넣은 상품 등의 관찰된 정보를 기반으로 하며, 개인의 사생활을 침해하지 않는 범위 내에서 이루어지도록 했다.

• Annals of Occupational and Environmental Medicine
• /
• v.35
• /
• pp.1.1-1.11
• /
• 2023

Background: Although it is well known that the usage of visual display terminal (VDT) at the workplace causes computer vision syndrome (CVS), previous studies mainly focused on computer use and the health of white-collar workers. In this study, we explored the relationship between the usage of VDT including various devices, and symptoms related to CVS in a large population including pink-collar workers and blue-collar workers. Methods: 21,304 wage workers over the age of 20 years were analyzed from the 6th Korean Working Conditions Survey. To investigate the association between VDT use at work and symptoms related to CVS among wage workers, odds ratios (ORs) and 95% confidence interval (CI) were calculated by multivariate logistic regression models. Results: In the group with the highest VDT usage at work, the OR of headache/eyestrain was 2.16 (95% CI: 1.86-2.52). The OR of suspected CVS patients was significantly increased in the highest group of usage of VDT at work (OR: 1.69; 95% CI, 1.39-2.06). Compare with the reference group, the OR for headache/eyestrain in the highest group of VDT usage was 2.81 (95% CI: 2.13-3.70) in white-collar workers, 1.78 (95% CI: 1.32-2.40) in pink-collar workers, and 1.59 (95% CI: 1.18-2.15) in blue-collar workers. Conclusions: We observed a relationship in which the use of VDT in the workplace increases the risk of headache/eyestrain regardless of occupational classification. Our findings emphasize the importance of paying attention to the health of VDT workers and making plans to improve their working conditions.

• The KIPS Transactions:PartB
• /
• v.9B no.4
• /
• pp.389-390
• /
• 2002

It is important that acquire information about if customer has some habit in electronic commerce application of internet base that led in recommendation service for customer in dynamic web contents supply. Collaborative filtering that has been used as a standard approach to Web personalization can not get rapidly user's preference change due to static user profiles and has shortcomings such as reliance on user ratings, lack of scalability, and poor performance in the high-dimensional data. In order to overcome this drawbacks, Web usage mining has been prevalent. Web usage mining is a technique that discovers patterns from We usage data logged to server. Specially. a technique that discovers Web usage patterns and clusters patterns is used. However, the discovery of patterns using Afriori algorithm creates many useless patterns. In this paper, the enhanced method for the construction of dynamic user profiles using validated Web usage patterns is proposed. First, to discover patterns Apriori is used and in order to create clusters for user profiles, ARHP algorithm is chosen. Before creating clusters using discovered patterns, validation that removes useless patterns by Dempster-Shafer theory is performed. And user profiles are created dynamically based on current user sessions for Web personalization.

• Korean Journal of Health Education and Promotion
• /
• v.22 no.4
• /
• pp.1-16
• /
• 2005

Objectives: This study was conducted to identify the computer game usage of elementary school children and their needs for education on the prevention of computer game addiction. Methods: The subjects of this study were 455 elementary school children. The data were collected from an open and structured questionnaire on the subjects' computer game usage and their needs for education on the prevention of computer game addiction. Results: The boys played computer games more than the girls. There were statistical differences in the durations of the computer game use, the main locations of the computer games they played, the times of the day when they used computers, the times of the day when they played computer games, the number of times in a week they visited Internet cafes, what motivated them to play computer games, and their partners in playing computer games according to gender. From an analysis of 714 statements of the subjects with respect to their need to be educated on computer game addiction prevention, six domains and 19 themes were drawn. The six main domains identified were Definition & Status, Etiology & Process, Influences, Prevention, Diagnosis & Coping with Computer Game Addiction, and General Information on Computer Games. This study results revealed that elementary school children have to be comprehensively educated on how to prevent computer game addiction. Conclusion: A computer game addiction prevention program concerning these themes and domains must be developed. A study should also be conducted to identify the educational needs of parents of elementary school children on computer game addiction prevention.

• Journal of the Korea society of information convergence
• /
• v.6 no.2
• /
• pp.61-66
• /
• 2013

In this study, the accounting information systems and Satisfaction with computerized accounting education study. As the control variable, computer usage time and computer experience were used. To sum up the analysis result, Details of the quality of accounting information system, quality system quality, information quality, service quality, satisfaction of computerized accounting education was analyzed significant effect. Used to control variable, computer usage time. Computer usage time of the control variable in the system quality, information quality and significant impact on satisfaction. Computer experience of the control variable in the system quality, information quality and significant impact on satisfaction.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.2 no.3
• /
• pp.204-209
• /
• 2002

The interest of data mining in artificial intelligence with fuzzy logic has been increased. Data mining is a process of extracting desirable knowledge and interesting pattern ken large data set. Because of expansion of WWW, web data is more and more huge. Besides mining web contents and web structures, another important task for web mining is web usage mining which mines web log data to discover user access pattern. The goal of web usage mining in this paper is to find interesting user pattern in the web with user feedback. It is very important to find user's characteristic fer e-business environment. In Customer Relationship Management, recommending product and sending e-mail to user by extracted users characteristics are needed. Using our method, we extract user profile from the result of web usage mining. In this research, we concentrate on finding association rules and verify validity of them. The proposed procedure can integrate fuzzy set concept and association rule. Fuzzy association rule uses given server log file and performs several preprocessing tasks. Extracted transaction files are used to find rules by fuzzy web usage mining. To verify the validity of user's feedback, the web log data from our laboratory web server.