• Journal of Digital Convergence
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• v.14 no.10
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• pp.167-172
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• 2016

Commercial analysis has been used for a lot of reasons such as improving the distribution structure, operational cost savings. However, existing commercial assay system is mostly flow through the analysis of the population and the environment around the store. Therefore, in this paper, we design a path weighted data analysis system for efficient product arrangement. It is not applying the analysis method of the existing commercial sales center but the data analysis system applying the weight to the form of customers' paths in a store. In conjunction with the existing POS system, it provides effective product placement in department stores, such as supermarkets, convenience stores. To this end, a system that maximizes efficiency of product placement in stores, receiving path data, converting them into statistics data that apply the weight, and printing out them into a visualized monitering system for the manager to see was designed.

• Journal of Intelligence and Information Systems
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• v.7 no.1
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• pp.97-121
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• 2001

Until now, we have believed that one of advantages of cyber market is that it can virtually display and sell goods because it does not necessary maintain expensive physical shops and inventories. But, in a highly competitive environment, business model that does away with goods in stock must be modified. As we know in the case of AMAZON, leading companies already consider merchandise management as a critical success factor in their business model. That is, a solution to compete against one's competitors in a highly competitive environment is merchandise management as in the traditional retail market. Cyber market has not only past sales data but also web log data before sales data that contains information of path that customer search and purchase on cyber market as compared with traditional retail market. So if we can correctly analyze the characteristics of before sales patterns using web log data, we can better prepare for the potential customers and effectively manage inventories and merchandises. We introduce a systematic analysis method to extract useful data for merchandise management - demand forecasting, evaluating & selecting - using web mining that is the application of data mining techniques to the World Wide Web. We use various techniques of web mining such as clustering, mining association rules, mining sequential patterns.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.875-878
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• 2007

Up until now, when a user search product information, the keyword-based search that mainly uses frequency of words or vocabulary information has been utilized in large. In the keyword-based research, the user should have to bear additional burden in order to search the displayed results manually once again because it shows those files that have no connection at all with the inquiries made by the user. To resolve such a problem, ontology has been emerged. In this paper, product search system using ontology was constructed directly and also tested how accurate search it does perform through the searching according to classification. To test this, about 40,000 product data of A discount store, which was operating on/off line discount stores, were constructed as database, and developmental environment for User Interface was tested by having developed the search system using JSP and PowerBuilder 9.0. Results from the test proved that the search method using Domain Ontology for product presented and designed in this paper was superior to the existing keyword-based search method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.7
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• pp.1318-1324
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• 2007

TSP(Traveling Salesman Problem) is a problem finding out the shortest distance out of many courses where given cities of the number of N, one starts a certain city and turns back to a starting city, visiting every city only once. As the number of cities having visited increases, the calculation rate increases geometrically. This problem makes TSP classified in NP-Hard Problem and genetic algorithm is used representatively. To obtain a better result in TSP, various operators have been developed and studied. This paper suggests new method of population initialization and of sequential transformation, and then proves the improvement of capability by comparing them with existing methods.

• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.203-216
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• 2022

In the recent business environment, purchase patterns are changing around the influence of COVID-19 and the online market. This study analyzed cluster and correlation analysis based on purchase and product information. The cluster analysis of new methods was attempted by creating customer, product, and cross-bonding clusters. The cross-bonding cluster analysis was performed based on the results of each cluster analysis. As a result of the correlation analysis, it was analyzed that more association rules were derived from a cross-bonding cluster, and the overlap rate was less. The cross-bonding cluster was found to be highly efficient. The cross-bonding cluster is the most suitable model for recommending products according to customer needs. The cross-bonding cluster model can save time and provide useful information to consumers. It is expected to bring positive effects such as increasing sales for the company.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.97-117
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• 2012

Nowadays, Internet users tend to do a variety of actions at the same time such as web browsing, social networking and multimedia consumption. While watching a video, once a user is interested in any product, the user has to do information searches to get to know more about the product. With a conventional approach, user has to search it separately with search engines like Bing or Google, which might be inconvenient and time-consuming. For this reason, a video annotation platform has been developed in order to provide users more convenient and more interactive ways with video content. In the future of smart TV environment, users can follow annotated information, for example, a link to a vendor to buy the product of interest. It is even better to enable users to search for information by directly discussing with friends. Users can effectively get useful and relevant information about the product from friends who share common interests or might have experienced it before, which is more reliable than the results from search engines. Social networking services provide an appropriate environment for people to share products so that they can show new things to their friends and to share their personal experiences on any specific product. Meanwhile, they can also absorb the most relevant information about the product that they are interested in by either comments or discussion amongst friends. However, within a very huge graph of friends, determining the most appropriate persons to ask for information about a specific product has still a limitation within the existing conventional approach. Once users want to share or discuss a product, they simply share it to all friends as new feeds. This means a newly posted article is blindly spread to all friends without considering their background interests or knowledge. In this way, the number of responses back will be huge. Users cannot easily absorb the relevant and useful responses from friends, since they are from various fields of interest and knowledge. In order to overcome this limitation, we propose a method to filter a user's friends for information search, which leverages semantic video annotation and social networking services. Our method filters and brings out who can give user useful information about a specific product. By examining the existing Facebook information regarding users and their social graph, we construct a user profile of product interest. With user's permission and authentication, user's particular activities are enriched with the domain-specific ontology such as GoodRelations and BestBuy Data sources. Besides, we assume that the object in the video is already annotated using Linked Data. Thus, the detail information of the product that user would like to ask for more information is retrieved via product URI. Our system calculates the similarities among them in order to identify the most suitable friends for seeking information about the mentioned product. The system filters a user's friends according to their score which tells the order of whom can highly likely give the user useful information about a specific product of interest. We have conducted an experiment with a group of respondents in order to verify and evaluate our system. First, the user profile accuracy evaluation is conducted to demonstrate how much our system constructed user profile of product interest represents user's interest correctly. Then, the evaluation on filtering method is made by inspecting the ranked results with human judgment. The results show that our method works effectively and efficiently in filtering. Our system fulfills user needs by supporting user to select appropriate friends for seeking useful information about a specific product that user is curious about. As a result, it helps to influence and convince user in purchase decisions.

• Journal of Bio-Environment Control
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• v.1 no.2
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• pp.135-141
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• 1992

Effects of various artificial light sources on the growth of Chinese white cabbage, Chinese flat cabbage, lettuce, garland chrysanthemum, and green perilla were investigated. Plants were grown under different treatments for three weeks. Generally, the growth of artificial light treatment were better than natural daylight(ND). The greatest growth and external quality occurred in high-pressure sodium lamp(HPS). In incandescent lamp(IL), fresh weight was heavy, but marketable quality was poor because of succulent(or spindly) growth. Overall, vitamin C content were no difference among treatments. But relative chlorophyll content was somewhat high in HPS.

• Korean Business Review
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• v.21 no.2
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• pp.171-194
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• 2008

In this study, specific review for the recent trend both in technical parts and the contents of IFE will be revealed. At the same time, how the passenger's satisfaction on IFE will lead to make an intention of repurchase and create the transmission of positive feed backs on the concerned airline has been thoroughly studied. In order to do the above, 250 air traveling passengers has participated the survey and 235 survey forms has been analyzed by Multiple Regression Analysis. According to the analysis, the physical environmental Improvement in aircraft system helps to Increase the satisfaction degree on IFE. The convenience is revealed as the most effective factor in the satisfaction degree on IFE while the atmosphere and design is regarded as the similarly Important factor. The contents of IFE are obviously affecting the satisfaction degree in positive side. Consequently, the customers' satisfaction on IFE positively affects to the repurchase intention especially to the transmission of the feed back.

• Bulletin of Korea Environmental Preservation Association
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• s.397
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• pp.6-9
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• 2012

우리나라는 세계 10위의 에너지 소비국이나 에너지의 97%를 수입에 의존하고 있는 실정으로 지난해는 약 1,600억 달러를 에너지 수입비용으로 지불했다. 이 수입액은 우리나라 3대 수출주력 상품인 반도체, 화공품, 선박을 합한 수출액과 맞먹는 것으로 에너지 가격변동에 극히 취약하고 국민의 삶의 질과 직결되고 있어 에너지 자주권 확보가 절실하다. 이에 대해 정부는 에너지 자주권 확보를 위해 노력하고 있으나 석유 가스의 자주개발률은 10.8%에 불과하여 전략적 완충 수준인 20% 확보는 요원해 보인다.

• Journal of the Ergonomics Society of Korea
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• v.10 no.2
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• pp.57-64
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• 1991

공업제품이나 소비자제품의 종류가 다양해지고 개방경제하에서의 국제적인 상품 유통과 산업교류가 증가함에 따라 인간이 사용하는 제품이나 환경의 안전성 , 편제성, 더나가서는 괘적성을 보장하기 위해서는 제품이나 환경의 설계, 제작, 생산, 및 유통에 있어 인간공학적인 검토가 소비자 보호의 측면에서 각국의 중요한 관심사로 대두되고 있다. 또한 산업사회가 발전함에 따라 인간-기계- 환경 사이의 합리적인 조화가 점점 더 중요하게 여겨지게 되어 인간공학분야의 국제표준화가 활발하게 이루어 지고 있다. 이러한 시점에서 그간 우리가 등한히 하여온 인간공학분야의 국제표준화 동향을 ISO( International Organization for Standardization) 의 활동을 중심으로 살펴보고자 한다.