• Journal of Cadastre & Land InformatiX
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• v.46 no.2
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• pp.283-296
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• 2016

This paper aims to analyze characteristic by the cities focused on the ratio of new apartment resale that is one of the apartment unit sale market, which has been increased recently. To do so, this study examined characteristics of population, housing, residential, and economical with 162 cities and counties and performed multiple regression analysis with dependent variable, ratio of new apartment resale. As a result. the factors affecting the ratio of new apartment resale are 7variables, regional apartment rate, population increasing rate, a mount of sell in lots, housing rent price (Jeonse price) rate compared to average apartment sale price, single-person households increasing rate, apartment subscription rate and number of buyers in the area. Thus, this study showed that the factors affecting characteristic by the regions are ordered characteristics of residential, population and rate of sale and dealing. Based on this result, this study will be basic data for policy of government and development of apartment sales system and for end user to activate resale in apartment sales market.

• The KIPS Transactions:PartB
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• v.14B no.2
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• pp.127-134
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• 2007

There are many researches about the intelligent stock trading systems with the help of the advance of the artificial intelligence such as machine learning techniques, Though the establishment of the reasonable trading policy plays an important role in the performance of the trading systems most researches focused on the improvement of the predictability. Also some previous works, which treated the trading policy, treated the simplified versions dependent on the predictors in less systematic ways. In this paper, we propose the integrated multiple simulation' as a method of optimizing trading performance of stock trading systems. The propose method is adopted in the NXShell a development environment for neural network based stock trading systems. Under the proposed integrated multiple simulation', we simulate the multiple tradings for all combinations of the neural network's outputs and the trading policy parameters, evaluate the learning performance according to the various metrics and establish the optimal policy for a given prediction module based on the resulting performance. In the experiment, we present the trading policy comparison results using the stock value data from the KOSPI and KOSDAQ.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.22-26
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• 2018

In this paper, we propose a model that classifies different transaction information by clustering and learning through similarity and transaction pattern of cryptocurrency transaction information. By using characteristics of genetic algorithms, we can get better clustering performance by eliminating unnecessary elements in clustering process. The transaction information including the clustering value is set as the training data, and the transaction information can be predicted through the classification algorithm. This can be used to automatically detect abnormal transactions from various transaction information of the cryptocurrency.

• Journal of Distribution Research
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• v.12 no.1
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• pp.105-123
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• 2007

Recently, the beauty service industry in Korea is growing rapidly as women have increased role in society and consumers have more diversified desire for beauty. In that sense, studies on the environment of transaction is necessary to maintain the customers who use beauty service which Is one of the most prominent services in Korea. However, there is a lack of systematic investigation on that. Under those circumstances, this study tries to propose strategies by shedding light on the reasons of store loyalty based on empirical study. Furthermore, securing regular customers is deemed to be the most important thing as the competition among stores are getting fiercer in the wake of increase in the number of beauty salons. In that light, this study tries to shed light on the transaction cost clearly which affects the store loyalty, and focuses on the development of integrated research model for the transaction cost related to the environmental characteristics of beauty service industry and for the store loyalty.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.11a
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• pp.337-340
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• 2006

FP-tree(Frequent Pattern Tree) 연관 규칙 탐사 알고리즘은 DB 스캔에 대한 부담을 획기적으로 절감시킴으로써 전체적인 성능을 향상시키고자 제안되었다. 그런데, FP-tree는 DB에 저장된 거래 내용중 빈발 항목을 포함하는 모든 거래를 트리에 저장해야 하기 때문에 그만큼 많은 메모리를 필요로 한다. 이 논문에서는 범용 운영체제인 유닉스 시스템을 사용해서 메모리 사용 측면에서 F.P. Tree 알고리즘의 타당성과 이에 따른 성능 특성을 관찰하였다. 그 결과, F.P. Tree 알고리즘은 현대 컴퓨터에서 보편화된 512MB${\sim}$1GB의 주메모리 시스템에서 무리는 없으나, 메모리 소요량이 DB의 크기나 빈발 항목 집합의 수 보다는 거래의 길이 등 DB의 특성에 따라 급격하게 증가하는 것으로 나타났다.

• The Journal of Society for e-Business Studies
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• v.10 no.2
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• pp.133-150
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• 2005

Electronic Trade is dramatically changing classical international trade paradigms. In particular, under the new economic environment, the ability to utilize and Information Technologies such as Electronic Data Interchange, Web-based EDI, ebXML, web service, Internet are emerging as an important factor in deciding the competitiveness of export business. The primary purpose of this study is (1) to investigate motivation factors and performance factors of electronic trade, (2) to show the relationship between motivation factors and the level of the utilization of e-trade, (3) to reveal the relationship between the level of the utilization and performance factors of e-trade. Analysis of survey questionnaire of Korean middle and small companies indicates the following : (1) motivation factors such as cost factor, education and promotion and the search of new market, have positive effect on the level of utilization of e-trade. (2) the level of utilization of e-trade has positive effect on the performance factors such as cost factor, the search of new market, the improvement of task process.

• Information Systems Review
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• v.23 no.4
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• pp.45-67
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• 2021

As the transaction volume of the C2C second-hand market is growing, the number of frauds, which intend to earn unfair gains by sending products different from specified ones or not sending them to buyers, is also increasing. This study explores the model that can identify frauds in the online C2C second-hand market by examining the postings for transactions. For this goal, this study collected 145,536 field data from actual C2C second-hand market. Then, the model is built with the characteristics from postings such as the topic and the linguistic characteristics of the product description, and the characteristics of products, postings, sellers, and transactions. The constructed model is then trained by the machine learning algorithm XGBoost. The final analysis results show that fraudulent postings have less information, which is also less specific, fewer nouns and images, a higher ratio of the number and white space, and a shorter length than genuine postings do. Also, while the genuine postings are focused on the product information for nouns, delivery information for verbs, and actions for adjectives, the fraudulent postings did not show those characteristics. This study shows that the various features can be extracted from postings written in C2C second-hand transactions and be used to construct an effective model for frauds. The proposed model can be also considered and applied for the other C2C platforms. Overall, the model proposed in this study can be expected to have positive effects on suppressing and preventing fraudulent behavior in online C2C markets.

• Journal of Korea Game Society
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• v.11 no.2
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• pp.45-56
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• 2011

The concept, means, value chain, the persons concerned and possible issues of game item trading in cash are analyzed in this study. The trading is characterized by not only being performed with its own unique business model but also causing issues related to delicate social problems, such as digital contents distribution, work place and gambling. The way of game item trading in cash and its value chain have been changed with game market growth for the past years. I analyzed in this article the new concept of game item trading in cash that is different from the past. Also, analysis on several issues related to game item trading in cash is conducted.

• Proceedings of the Korean DIstribution Association Conference
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• 2006.08a
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• pp.155-173
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• 2006

본 연구는 기업의 이윤에 직접적인 영향을 미치는 거래비중을 결정하는 데 있어, 고객가치가 갖는 영향력 및 고객가치 향상을 위해 해당 기업이 갖춰야 할 요건이 무엇인가를 규명하고 있다. 대부분의 기업 간 관계가 복수의 형태를 취하고 있는 현실에 비해, 가치의 선행요소를 규명하는 데 있어서 기존의 연구들은 주로 이원적인 관계에 국한된 연구를 수행함으로써, 실제 유통경로가 처한 상황을 충분히 설명하지 못한다는 한계가 있어왔다. 본 연구에서는 기업의 가치창출 활동이 경쟁우위와 관련되어 있다는 전략이론의 관점을 바탕으로 가치의 선행요소를 규명하고 있다. 연구 결과 가치의 구성요소인 관계혜택과 거래비용은 기업의 거래비중을 결정하는데 결정적인 역할을 하는 것으로 나타났으며, 특히 관계혜택이 거래비용에 비해 상대적으로 더 큰 영향력을 갖는 것으로 밝혀졌다. 가치의 선행요소에 있어서는 기업이 가진 자원에 초점을 맞춘 Resource-based view를 기반으로 한 변수들에 비해, 다른 기업과의 관계에 주목한 Relational view에 관련된 변수들이 고객가치 창출에 더 큰 영향력을 갖고 있음을 알 수 있었다. 추가적으로 행해진 환경의 불확실성의 조절효과를 규명 결과, 환경의 불확실성은 주로 Relational view를 기반으로 하는 관계적 특성에 영향을 미치는 것으로 나타났다.

• Review of KIISC
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• v.13 no.3
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• pp.72-82
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• 2003

XML(extensible Markup Language)은 인터넷 기반 정보시스템의 정보 교환 양식으로 그 활용도가 증가하고 있으며, 여러 형태의 문서를 통합하고 전달하는 전자거래의 표준으로 인식되고 있다. 이러한 환경에서 전자거래 시 교환되는 XML 문서의 보다 안전한 보안 서비스를 하기 위한 방안으로 새로운 기술과 기존의 기술들을 융합할 수 있는 모듈화 되고 확장된 보안 기술이 필요하다. XML 정보보호기술 중 XML 키 관리 명세(XKMS)는 다양하고 복잡한 기능의 전자거래 어플리케이션에서 XML 문서의 서명을 검증하거나 암호화하는 공개키의 관리를 위한 프로토콜을 정의한다. 본 고에서는 XML 기반 보안서비스 특성에 착안하여 안전한 전자거래를 위한 XML 키 관리 기술과 표준화 과정에서 논의되고 있는 기술적 이슈에 대해 살펴보고 국내외 동향을 알아보고자 한다.