• Journal of Digital Convergence
• /
• v.10 no.1
• /
• pp.203-213
• /
• 2012

This paper attempts to find out the psychological characteristic factors of Korean consumers, and to identify how they influence consumers' attitudes toward the products for the world famous brands. The related literature refers face-consciousness trait, boast trait and ritualism trait to the main research objectives of this research. As results, 3 underlying factors are found to underly the 'Chemyon(social face)', 6 factors to 'Uzzul(Boasting)'. Multiple regression analysis reports that 'Uzzul(Boasting)' trait has a significant influence over the consumer's attitudes toward the product for the famous brands, and Chemyon(social face) trait has the same effects as well though with less statistical weight. The paper's findings suggests academically that we need more serious research endeavor to understand consumption propensities that are salient to Korean consumers. And, they also imply that advertising creative director would implement the knowledge in developing creative strategy for brand advertising.

• Journal of Elementary Mathematics Education in Korea
• /
• v.19 no.3
• /
• pp.347-370
• /
• 2015

The purpose of this study is to examine the effects of mathematical modeling activities on mathematical problem solving abilities and mathematical dispositions in elementary school students. For this study, we administered mathematical modeling activities to fifth graders, which consisted of 8 topics taught over 16 classes. In the results of this study, mathematical modeling activities were statistically proven to be more effective in improving mathematical problem solving abilities and mathematical dispositions compared to traditional textbook-centered lessons. Also, it was found that mathematical modeling activities promoted student's mathematical thinking such as communication, reasoning, reflective thinking and critical thinking. It is a way to raise the formation of desirable mathematical dispositions by actively participating in modeling activities. It is proved that mathematical modeling activities quantitatively and qualitatively affect elementary school students's mathematical learning. Therefore, Educators may recognize the applicability of mathematical modeling on elementary school, and consider changing elementary teaching-learning methods and environment.

• Journal of KIISE:Software and Applications
• /
• v.36 no.2
• /
• pp.144-152
• /
• 2009

To provide intelligent service in mobile environment, it needs to estimate user's intention or requirement, through analyzing context information of end-users such as preference or behavior patterns. In this paper, we infer context information from uncertain log stored in mobile device. And we propose the inference method of end-user's behavior to match context information with service, and the proposed method is based on context-tree. We adopt bayesian probabilistic method to infer uncertain context information effectively, and the context-tree is constructed to utilize non-numerical context which is hard to handled with mathematical method. And we verify utility of proposed method by appling the method to intelligent phone book service.

• Journal of Digital Convergence
• /
• v.10 no.2
• /
• pp.293-297
• /
• 2012

In order to provide with personalized recommendation service in context-awareness environment, the collected context data should be analyzed fast and the objective of user should be able to inferred effectively. But, the context collected from the mobile devices is not suitable for applying the existing inference algorithms as they are due to the omission or uncertainty of information and the efficient algorithms are required for mobile environment. In this paper, the behavior pattern was classified using naive bayes classification for minimize the loss caused by the omission or error of information. And pattern matching was used to effectively learn of the users inclination and infer the behavior purpose. The accuracy of the suggested inference model was evaluated by applying to the application recommendation service in the smart phones.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2005.04a
• /
• pp.241-244
• /
• 2005

최근 로봇의 개발 경향은 인간과 로봇이 공존하면서 서비스를 제공하는 로봇의 개발이 지속적으로 증가하는 추세이다. 인간은 자신의 성향에 맞게 능동적인 역할 수행하는 서비스 로봇을 요구한다. 하지만 일률적으로 생산된 서비스 로봇은 다양한 사람들의 개성을 모두 충족시키지 못하고 있다. 그래서 사용자의 환경, 상황을 인식하고 사용자의 성향에 맞는 행동을 지능적으로 판단하고 대처할 수 있는 로봇이 요구된다. 본 논문에서는 주변 환경을 평가하고 로봇이 스스로 행동할 수 있는 지능형 알고리즘을 제안하고자 한다. 다수 입력을 통해 제어할 수 있도록 퍼지 룰을 이용하여 추론하였다.

• Proceedings of the Korean Information Science Society Conference
• /
• 2005.11a
• /
• pp.787-789
• /
• 2005

기존의 운영체제에서는 시스템이 프로세스의 종류를 알지 못하므로, 사용자가 명시하지 않은 서로 다른 종류의 프로세스에 모두 동일한 스케줄링 정책을 적용해 왔다. 따라서 한번 결정된 스케줄링 정책은 변화하는 환경에 적응하지 못한다는 단점이 있다. 본 논문에서는 리눅스 환경에서 프로세스들의 자원사용량을 근거로 각 프로세스를 일괄처리 프로세스, 대화식 프로세스, 실시간 프로세스로 분류하고, 각 분류에 대한 사용자 우선순위를 모델링하여 사용자의 성향에 맞게 프로세스에 우선순위를 부여하는 사용자 적응적 프로세스 스케줄링 기법을 제안한다. 이 방법은 사용자의 성향에 따라서 스케줄링 정책을 결정할 수 있으며, 여러 사용자에게 서로 다른 스케줄링 정책을 적용할 수 있다. 실험 결과 제안하는 방법의 유용성을 확인할 수 있었다.

• Journal of the Korea Society of Computer and Information
• /
• v.8 no.1
• /
• pp.20-29
• /
• 2003

According as quantity of information is augmented rapidly in World Wide Web, users are investing more times finding correct information to on. Search function that a search agent is personalized according to user's preference degree or search objective to solve these problem should be offered. Therefore, a search agent accumulates experienced knowledge connected with user's past search in this research. When new query was given, search agent offered learning function of intelligence that decides category group through estimation method of similarity using this knowledge. So this paper showed that case based search can bring superior result in the correctness rate than other search method.

• Journal of the Korea Society for Simulation
• /
• v.19 no.4
• /
• pp.59-66
• /
• 2010

We present a personalized clothing recommender system - one that mines association rules from transaction described in ontologies and infers a recommendation from the rules. The recommender system can forecast frequently changing trends of clothing using the Onto-Apriori algorithm, and it makes appropriate recommendations for each users possible through the inference marked as meta nodes. We simulates the rule generator and the inferential search engine of the system with focus on accuracy and efficiency, and our results validate the system.

• Proceedings of the Korean Information Science Society Conference
• /
• 2008.06c
• /
• pp.95-99
• /
• 2008

유비쿼터스 환경에서 사용자는 개인용 디바이스를 이용하여 보이지 않는 수많은 자원들과 서로 연결하여 원하는 서비스를 제공 받기를 원한다. 이러한 요구사항을 만족시키기 위하여 유비쿼터스 지능 공간에 존재하는 자원들 사이의 공유가 필요하며 이를 효율적으로 수행하기 위한 연구는 새로운 연구 주제이다. 그러나 동일한 환경이라 할 지라도 각 사용자들의 상황은 서로 다르며 개인적인 성향 역시 다양하다. 그러므로 동일한 공간에서 동일한 서비스를 원하는 사용자들이라 할 지라도 현재의 상황과 사용자 개개인의 개성에 따라 필요로 하는 자원이 다른 것이 현실이다. 그러므로 본 논문에서는 사용자의 상황을 인지하여 맞춤형 자원을 추천하는 시스템을 개발한다. 추천 시스템은 사용자의 상황을 인지하기 위한 방법으로 온톨로지 기반 추론을 수행하고, 개인화 추천 서비스를 제공하기 위하여 규칙들 이용한 규칙 기반 추론 방법을 수행한다.

• Journal of Digital Convergence
• /
• v.13 no.9
• /
• pp.269-276
• /
• 2015

Recently, with the activation of the industry related to the big data, the global security companies have expanded their scopes from structured to unstructured data for the intelligent security threat monitoring and prevention, and they show the trend to utilize the technique of user's tendency analysis for security prevention. This is because the information scope that can be deducted from the existing structured data(Quantify existing available data) analysis is limited. This study is to utilize the analysis of security tendency(Items classified purpose distinction, positive, negative judgment, key analysis of keyword relevance) applying the machine learning algorithm($Na{\ddot{i}}ve$ Bayes, Decision Tree, K-nearest neighbor, Apriori) in the big data environment. Upon the capability analysis, it was confirmed that the security items and specific indexes for the decision of security tendency could be extracted from structured and unstructured data.