• Proceedings of the Korean System Dynamics Society
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• 2002.08a
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• pp.69-78
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• 2002

물리공간을 제1공간, 전자공간을 제2공간이라고 한다면 이들의 결합을 통하여 새로이 등장할 공간은 3의 공간이다. 대형 컴퓨터 시대에는 컴퓨터가 희소 자원이었고 (1대 컴퓨터 - 다 사용자), 개인용 컴퓨터(PC) 시대에는 (1대 컴퓨터 - 1 사용자)였으며, 유비쿼터스 컴퓨팅의 시대에는 (다 컴퓨터 - 1 사용자) 시대가 된다. 사용자와 컴퓨터 그리고 통신기기간에 존재하는 희소성의 역전은 이미 가시화되고 있다. 더 이상 컴퓨터와 통신기기는 희소자원이 아니다. 오히려 사용자가 희소해 진다. 지천으로 잘린 컴퓨터들은 사용자가 자신을 이용해 주기를 조용히 기다린다(중략)

• Proceedings of the Korean System Dynamics Society
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• 2004.02a
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• pp.83-108
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• 2004

ㆍ정부규제의 개념 -정부 규제는 민간활동 주체의 행위를 유인 또는 강제함으로써 공익을 실현하는 수단 -외부 경제효과, 독과점에 의한 폐해, 담합 담지 등을 통한 소비자 효익 증진이 목적 -산업 경쟁력 저하하는 비능률적 관행으로 인식 ㆍ이동 통신 시장에서의 정부 규제 -비대칭으로 특징지워지는 많은 규제 이슈들이 제기되고 있음 -이는 다음의 경쟁 특성에 기인함 (1) 자본 집약성으로 인한 과점적 시장 구조 (2) 번호 이동성의 결여 (3) 네트워크 효과 (4) 상호접속을 통한 경쟁사간 생산요소 공급 (5) 주파수 대역의 희소성(중략)

• Proceedings of the Korean Institute of Surface Engineering Conference
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• 2016.11a
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• pp.167.1-167.1
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• 2016

금도금은 장식용 핸드백이나 가방 등에 주로 사용하고 있으며, 이러한 금을 도금하면 장식성이 최대로 되어 고객을 만족시킬 수 있다. 금도금은 초기에는 주로 외관의 장식용에 사용 되었으나, 이후 디자인과 기능성부품으로 이용이 확대되었다. 현재 국내의 금 사용량과 수요량은 매년 급증하고는 있지만 희소성, 지역편중성, 공급불안정과 이에 따른 가격불안정성과 같은 자원적 문제를 갖고 있을 뿐만 아니라 전량 수입에 의존하고 있다. 유럽, 특히 이탈리아의 금도금의 기술동향을 제공함으로써 매출증대를 향상시킬 수 있다. 이러한 금도금기술은 수출용 액세서리 등의 분야로 적용이 확대되고 있다.

• Journal of the Korean Society of Clothing and Textiles
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• v.33 no.10
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• pp.1519-1529
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• 2009

This study investigates the influences of the impulse buying tendency of consumers, apparel price and scarcity messages on purchasing behavior at the time of purchase on the internet. This study was comprised of 2 (impulse buying: high versus low) $\times$ 2 (price of Internet purchase products: high apparel price versus low apparel price) $\times$ 2 (scarcity message: quantity scarcity message versus time scarcity message) with three mixed elements. The subjects of this study were 400 college students in the Seoul and Gyeonggi area. A total of 95 students who had a high tendency for impulsive purchase and 104 who had a low tendency participated in the survey. Data are analyzed by factor analysis, T-test, and ANOVA. The results of this study are as follows. 1. At the time of group buying on the Internet, impulse buying tendency, apparel price, and scarcity message had a statistically significant interaction effect on consumer preferences. 2. At the time of purchase on the Internet, impulse buying tendency, apparel price, and scarcity message did not have a statistically significant interaction effect on the intention of consumers to make a purchase. However, there was a significant difference in the intention to make a purchase based on impulse buying tendency and apparel price.

• Journal of the Korea Society of Computer and Information
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• v.24 no.12
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• pp.93-100
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• 2019

Similarity computation is very crucial to performance of memory-based collaborative filtering systems. These systems make use of user ratings to recommend products to customers in online commercial sites. For better recommendation, most similar users to the active user need to be selected for their references. There have been numerous similarity measures developed in literature, most of which suffer from data sparsity or cold start problems. This paper intends to extract preference information as much as possible from user ratings to compute more reliable similarity even in a sparse data condition, as compared to previous similarity measures. We propose a new similarity measure which relies not only on user ratings but also on movie genre information provided by the dataset. Performance experiments of the proposed measure and previous relevant measures are conducted to investigate their performance. As a result, it is found that the proposed measure yields better or comparable achievements in terms of major performance metrics.

• The Journal of Korean Association of Computer Education
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• v.19 no.4
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• pp.59-66
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• 2016

It has been studied to reflect the number of co-rated items for solving data sparsity problem in collaborative filtering systems. A well-known method of Jaccard index allowed performance improvement, when combined with previous similarity measures. However, the degree of performance improvement when combined with existing similarity measures in various data environments are seldom analyzed, which is the objective of this study. Jaccard index as a sole similarity measure yielded much higher prediction quality than traditional measures and very high recommendation quality in a sparse dataset. In general, previous similarity measures combined with Jaccard index improved performance regardless of dataset characteristics. Especially, cosine similarity achieved the highest improvement in sparse datasets, while similarity of Mean Squared Difference degraded prediction quality in denser sets. Therefore, one needs to consider characteristics of data environment and similarity measures before combining Jaccard index for similarity use.

• Environmental and Resource Economics Review
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• v.14 no.1
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• pp.221-235
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• 2005

In this paper, we analyzed the dynamic structure of optimal tariff levied on importing non-renewable resources such as petroleum, iron, coal, etc. According to the previous literature that have studied this objective, the time inconsistent open loop tariff has been suggested to be imposed in order to improve the welfare level of importing country. We set up the efficient model to identify how to impose the optimal tariff over time. Based on this model, we have found that the previous literature ignored that the costate variable for the stock for non-renewable resource decomposed between the scarcity effect and the cost effect. On the basis of the role of costate variable, we, however, have found that the proposition of the previous literature has led into errors. Hence, we suggest that the dynamically consistent open loop tariff for non-renewable resources would improve the welfare level of importing country.

• School Mathematics
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• v.16 no.1
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• pp.1-17
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• 2014

Mathematical creativity in school mathematics is connected with problem solving. The purpose of this study was to analyse elementary students' the mathematical creativity using multiple solution tasks which required to solve a mathematical problem in different ways. For this research, I examined and analyzed the response to four multiple solution tasks according to the evaluation system of mathematical creativity which consisted of the factors of creativity(fluency, flexibility, originality). The finding showed that mathematical creativity was different between students with greater clarity. And mathematical creativity in tasks was different. So I questioned the possibility of analysis of students' the mathematical creativity in mathematical areas. According to the evaluation system of mathematical creativity of this research, mathematical creativity was proportional to the fluency. But the high fluency and flexibility was decreasing originality because it was easy for students to solve multiple solution tasks in the same ways. So, finding of this research can be considered to make the criterion in both originality in rare and mathematical aspects.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.2
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• pp.205-211
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• 2012

The retrieved documents have to be transformed into proper data structure for the clustering algorithms of statistics and machine learning. A popular data structure for document clustering is document-term matrix. This matrix has the occurred frequency value of a term in each document. There is a sparsity problem in this matrix because most frequencies of the matrix are 0 values. This problem affects the clustering performance. The sparseness of document-term matrix decreases the performance of clustering result. So, this research uses the factor score by factor analysis to solve the sparsity problem in document clustering. The document-term matrix is transformed to document-factor score matrix using factor scores in this paper. Also, the document-factor score matrix is used as input data for document clustering. To compare the clustering performances between document-term matrix and document-factor score matrix, this research applies two typed matrices to self organizing map (SOM) clustering.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.1-18
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• 2016

Collaborative Filtering (CF) predicts the focal user's preference for particular item based on user's preference rating data and recommends items for the similar users by using them. It is a popular technique for the personalization in e-commerce to reduce information overload. However, it has some limitations including sparsity and scalability problems. In this paper, we use a method to integrate social network information into collaborative filtering in order to mitigate the sparsity and scalability problems which are major limitations of typical collaborative filtering and reflect the user's qualitative and emotional information in recommendation process. In this paper, we use a novel recommendation algorithm which is integrated with collaborative filtering by using Social SVD++ algorithm which considers social network information in SVD++, an extension algorithm that can reflect implicit information in singular value decomposition (SVD). In particular, this study will evaluate the performance of the model by reflecting the real-world user's social network information in the recommendation process.