• Imaging Science in Dentistry
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• v.32 no.3
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• pp.129-134
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• 2002

Purpose : To implement the database system of oral and maxillofacial radiological images using a commercial medical image management software with personally developed classification code. Materials and methods : The image database was built using a slightly modified commercial medical image management software, Dr. Image v.2.1 (Bit Computer Co., Korea). The function of wild card '*' was added to the search function of this program. Diagnosis classification codes were written as the number at the first three digits, and radiographic technique classification codes as the alphabet right after the diagnosis code. 449 radiological films of 218 cases from January, 2000 to December, 2000, which had been specially stored for the demonstration and education at Dept. of OMF Radiology of Dankook University Dental Hospital, were scanned with each patient information. Results: Cases could be efficiently accessed and analyzed by using the classification code. Search and statistics results were easily obtained according to sex, age, disease diagnosis and radiographic technique. Conclusion : Efficient image management was possible with this image database system. Application of this system to other departments or personal image management can be made possible by utilizing the appropriate classification code system.

• Journal of the Korean Society of Clothing and Textiles
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• v.41 no.5
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• pp.796-808
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• 2017

This research shows how fashion curation service consumers (both fashion and image consultants) reveal different aspects towards a preferred image type among the correlation of fashion curation service usage motivation and fashion shopping propensity. These preferences also included the purchase intentions for fashion display service products. This study surveyed 300 men and women between the ages of 20-30 who were the main consumers of fashion curation services. 'Convenience, fashion trend, and exploratory' increased purchase intentions for fashion shopping propensity, 'information search for utility, entertainment, and personal expression' increased purchase intentions for fashion curation services and 'brand identity, consumer lifestyle, and product information' increased factors for the fashion curation service preferred image type. Consumer preferences varied according to different fashion curation service image type; however, all consumer group syndicated a difference in fashion curation service actions. For instance, fashion curation service consumers preferred a consumer lifestyle image, convenience, hedonic shopping orientation, and personal expression motivation had a positive influence on product purchase intention. However, the shopping orientation of 'fashion trend, practical information exploration, and entertainment motivation' had an optimistic influence on product purchase intentions for fashion curation service consumers who preferred a brand identity image and a product information image.

• 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 Digital Convergence
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• v.10 no.1
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• pp.309-315
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• 2012

The dissemination of smartphones is being spread and supplementary services using smartphones are increasing and various as the Mobile network and device are developing rapidly, so smartphones that enables to provide a wide range of services is expected to receive the most attention. It makes users listen to music anytime, anywhere in real-time, use useful applications, and access to Internet to search for information. The service environment is changing on PC into Mobile due to the change of the circumstance mentioned above. these services are done by using just location information rather than other context, and users have to search services and use them. It is essential to have Context-aware technology for personalization recommendation services and the appropriate representation and definition of Context information for context-aware. Ontology is possible to represent knowledge freely and knowledge can be extended by inferring. In addition, design of the ontology model is needed according to the purposes of utilization. This paper used context-aware technologies to implement a user personalization recommendation service. It also defined the context through OWL modeling for user personalization recommendation service and used inference rules and inference engine for context reasoning.

• Journal of the Korean Institute of Landscape Architecture
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• v.21 no.3
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• pp.89-98
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• 1993

It is necessary for the park tree manager to have the current information about the status of trees, which can help him with right decisions. However, there are many problems in the existing management method such as huge amount of data, tedious work, and the difficult update work due to the lack of necessary data or the inappropriate data record and management method. The sole use of database management system(DBMS) cannot slove these problems because it cannot handle graphic data based on the locational information. So, it is imperative for the park manager to have locational data as well as attribute data of the park tree concerned. Therefore, the purpose of this study is to develop the personal computer-based, user friendly park tree management information system, which deals with attribute data(DBMS) and graphic data(using the CAD) together within the integrated environment. The park tree management information system developed in this study provides a complete operating environment for data input, update, query, delete, and retrieve. The major advantages of this system are as follows: 1) To search the location and distribution of trees. 2) To record, store, and manage data easily. 3) When the manager is changed, delivery of the park tree work is convenient. 4) The system can help the manager with the correct information for the efficient park tree management.

• Journal of Korea Multimedia Society
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• v.17 no.6
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• pp.671-680
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• 2014

Recently, with the remarkable increase of social network services, it is necessary to extract interesting information from lots of data about various individual opinions and preferences on SNS(Social Network Service). The sentiment information can be applied to various fields of society such as politics, public opinions, economics, personal services and entertainments. To extract sentiment information, it is necessary to use processing techniques that store a large amount of SNS data, extract meaningful data from them, and search the sentiment information. This paper proposes an efficient method to extract sentiment information from various unstructured big data on social networks using HDFS(Hadoop Distributed File System) platform and MapReduce functions. In experiments, the proposed method collects and stacks data steadily as the number of data is increased. When the proposed functions are applied to sentiment analysis, the system keeps load balancing and the analysis results are very close to the results of manual work.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.1B
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• pp.37-42
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• 2011

The change in performance of the mobile communication field took place due to jumping development of technology, so high performance terminals that anyone can directly search and amend desired information anywhere and anytime, namely, the mobile communication terminals called Smartphone were released to the market. The terminal can store informations that an individual stored, for example, call log, where to make contact and address of acquaintances, transmit/receive message and mail, photographs and videos, etc., but there are worries on surreptitious use of other people due to leaking of personal information through loss or theft of these terminals because of several reasons, so the present thesis aims to realize a method that remotely control information inside a terminal in case of loss of a mobile communication terminal.

• Journal of the Korean Society of Clothing and Textiles
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• v.21 no.3
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• pp.641-654
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• 1997

The purpose of this study is to investigate the relationship between the consumer's product knowledge and his/her ability to obtain information when buying clothing. For the purpose of this study, questionnaires were given to 550 university students living in Seoul and the Kwgi area. The questionnaires were designed to measure the consumer's knowledge about examine his/her method of gathering information and to obtain some personal information Vsing a base of 407 students, data was analyzed through cross- tabulation, the chi square test, the t-test, the one-way ANOVA accompanied by a post-hoc analysis with the Tukey method, Pearson's correlation coefficient, and the Spearman rho. The results of this study were as follows. 1) There was a significant difference in the amount of iuormation seeking between groups with different knowledge related to clothing. 2) The use of information sources was found to be significantly related to the consumer's subjective and objective knowledge. 3) The consumer's level of knowledge about clothing was related to the store characteristics that he/she took into consideration. The difference between the groups came from the number of store characteristics taken into consideration, rather than from the contents. The group that had more knowledge related to clothing was more aware of store characteristics than the other level stoup. Price, quality, uniqueness, and variety of clothing were equally important to by groups. 4) A moderate relationship was found between the consumer's subjective and objective knowledge, and between his/her purchasing experience and objective knowledge. There was a relatively high relationship between purchasing experience and subjective knowledge.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.8
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• pp.1865-1872
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• 2013

The social network services are grown rapidly through dissemination of smart devices. Therefore, increasing the data exponentially because many people use web services. Using these big data, it will be needed study of providing customized knowledge. So in this paper, we had collected data of 40 people for implementation of knowledge service using big data during one month. Based on these data, we had inferred information of location and moving type, and evaluated accuracy. Through that we had studied personal experience knowledge evaluation model for knowledge service.

• Journal of the Korean Society for Library and Information Science
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• v.47 no.4
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• pp.143-167
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• 2013

The power of human capital in a library is the main resource that determines the level of library services, which in turn should play a pivotal role in forming the intellectual power of the country. This research conducted a survey on the employment perspectives of LIS undergraduates, which resulted as follows. First, among the LIS undergraduates, 40% of students responded that their desire was to be employed in the library as librarians. Although there were some negative opinions regarding the working environment of the industry, the undergraduates appreciated the developmental possibilities. Second, the most desired task was working with cultural programs. Third, the respondents were satisfied with the current curriculum overall, acknowledging the extra need for job search support programs, which include career support, employment-related mentoring, and internships. Fourth, the main requirements for their future employability were perceived as grade point average, language skills, obtaining licenses, internship and apprenticeship experience, and career management. Fifth, influential factors on employment decision making were divided into two aspects: environmental and personal factors. The environmental factors included salary, welfare, opportunities in personal development, workplace environment, organizational culture, and development possibilities of the organization. The personal factors included fitness with personal aptitude, the level of knowledge and technology in the job industry, social norms and acknowledgement, rewarding opportunities with their major, and location of job.