• Journal of the Korea Furniture Society
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• v.20 no.2
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• pp.122-135
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• 2009

The objective of this work was to research click profile of laminate flooring by comparison of click and bonding laminate floorings, especially base on the click profile shape, bonding strength and international patents. Non-glue locking system has been used since laminate flooring was developed. For the reason of environment and saving installation time, the manufacturer in Europe and USA has developed click profile for laminate flooring. Each manufacturer has patent on each click profile. Although each click profile has good lock strength as shape, Berryand Unilin company's click profile systems showed higher locking strength than others. Korean laminate flooring company pay the fee of patent for using European and American manufacturer's click profile. From this work, we grope Korean style laminate flooring and click profile through research on the click profile shape, bonding strength and patents of European and American manufacturers.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.324-331
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• 2005

In this paper, we propose a new customer profile model based on customer behavior in Internet shopping mall. The proposed technique defines customer profile model based on customer behavior information such as click data, buy data, and interest categories. We also implement CBCPM(Customer Behavior-based Customer Profile Model) and perform extensive experiments. The experimental results show that CBCPM has higher precision, recall, and F1 than the existing customer profile model.

• International Journal of Internet, Broadcasting and Communication
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• v.8 no.3
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• pp.1-11
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• 2016

This study investigates whether different SNS with different characteristics have different impacts on participatory social capital in Korea. At least in Korea, SNS are categorized into five types (community, blog, micro-blog, profile-based service and instant message service), and participatory social capital is specified by three types (off-line political participation, on-line political participation, on-line civic engagement). Using Nielsen KoreanClick's web-based survey data, our regression analysis shows that SNS which are more open and focused on information sharing contribute more to participatory social capital.

• Radiation Oncology Journal
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• v.20 no.4
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• pp.375-380
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• 2002

Purpose : To develop a practical film dosimetry system for routine Quality Assurance (QA). Materials and Methods :An One Click Film (OCF) Dosimetry system was designed to perform swift routine QA with functions including automatic fog value elimination, angle adjustment, automatic symmetry calculation, and realtime profile generation with the ability to display realtime three-dimensional dose distributions. Results : The most frequently used functions for routine QA, such as the elimination of the fog value, conversion into an H&D curve, symmetry, and isodose distribution, can be achieved with only one click. Conclusion : Reliable results were achieved with the OCF dosimetry with simpler steps than other commercially available film dosimetry systems for routine QA. More research on the refined user interface will make this system be clinically useful.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.3
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• pp.587-594
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• 2019

This paper proposes a personalized web search technique that produces ranked results reflecting user's query intents and individual interests. The performance of personalized search relies on an effective users' profiling strategy to accurately capture their interests and preferences. User profile is a data set of words and customized weights based on recent user queries and the topic words of web documents from their click history. Personal profile is used to expand a user query to the personalized query before the web search. To determine the exact meaning of ambiguous queries and topic words, this strategy uses WordNet to calculate semantic similarities to words in the user personal profile. Experimental results with query expansion and re-ranking modules installed on general search systems shows enhanced performance with this personalized search technique in terms of precision and recall.

• Korean Management Science Review
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• v.23 no.3
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• pp.183-194
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• 2006

In this paper, we propose a customer profiling technique based on customer behavior for personalized products recommendation in Internet shopping mall. The proposed technique defines customer profile model based on customer behavior Information such as click data, buying data, market basket data, and interest categories. We also implement CBCPT(customer behavior based customer profiling technique) and perform extensive experiments. The experimental results show that CBCPT has higher MAE, precision, recall, and F1 than the existing other customer profiling technique.

• Soft Computing and Machine Intelligence
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• v.1 no.1
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• pp.31-35
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• 2021

In recent years, due to COVID-19, the process of shopping has become more restricted and difficult for customers. Based on this aspect, customers are more interested in online shopping to keep the Untact rules and stay safe, similarly ordering their product based on their need and interest with most straightforward and fastest ways. In this paper, the reinforcement learning technique is applied in the product recommendation system to improve the recommendation system quality for better and more related suggestions based on click patterns and users' profile information. The dataset used in this system was taken from an online shopping mall in Jeju island, South Korea. We have compared the proposed method with the recent state-of-the-art and research results, which show that reinforcement learning effectiveness is higher than other approaches.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.2
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• pp.690-696
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• 2016

Search engines that rely on morphological matching of user query and web document content do not support individual interests. This research proposes a personalized web search scheme that returns the results that reflect the users' query intent and personal preferences. The performance of the personalized search depends on using an effective user profiling strategy to accurately capture the users' personal interests. In this study, the user profiles are the databases of topic words and customized weights based on the recent user queries and the frequency of topic words in click history. To determine the precise meaning of ambiguous queries and topic words, this strategy uses WordNet to calculate the semantic relatedness to words in the user profile. The experiments were conducted by installing a query expansion and re-ranking modules on the general web search systems. The results showed that this method has 92% precision and 82% recall in the top 10 search results, proving the enhanced performance.

• Journal of KIISE:Software and Applications
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• v.35 no.8
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• pp.522-528
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• 2008

Topic map typically provide information to user through the selection of topics, that is using only topic, association, occurrence on the first topicmap which is made by domain expert without regard to individual interests or context, for the purpose of supplementation for the weakness which is providing personalized topic map information, personalization has been studied for supporting user preference through preseting of customize, filtering, scope, etc in topic map. Nevertheless, personalization in current topicmap is not enough to user so far. In this paper, we propose a design of PTRS(personalized topicmap ranking system) & algorithm, using both user profile(click through data) and basic element of topic map(topic, association) on knowledge layer in specific domain topicmap, therefore User has strong point that is improvement of personal facilities to user through representation of ranked topicmap information in consideration of user preference using PTRS.

• International Journal of Computer Science & Network Security
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• v.21 no.2
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• pp.171-180
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• 2021

Currently, hospitals and medical practices have a large amount of unstructured information, gathered in time at each ward or practice by physicians in a wide range of medical branches. The data requires processing in order to be able to extract relevant information, which can be used to improve the medical system. It is useful for a physician to have access to a patient's entire medical history when he or she is in an emergency situation, as relevant information can be found about the patient's problems such as: allergies to various medications, personal history, or hereditary collateral conditions etc. If the information exists in a structured form, the detection of diseases based on specific symptoms is much easier, faster and with a higher degree of accuracy. Thus, physicians may investigate certain pathological profiles and conduct cohort clinical trials, including comparing the profile of a particular patient with other similar profiles that already have a confirmed diagnosis. Involving information technology in this field will change so the time which the physicians should spend in front of the computer into a much more beneficial one, providing them with the possibility for more interaction with the patient while listening to the patient's needs. The expert system, described in the paper, is an application for medical diagnostic of the most frequently met conditions, based on logical programming and on the theory of probabilities. The system rationale is a search item in the field basic knowledge on the condition. The web application described in the paper is implemented for the ward of pathological anatomy of a hospital in Romania. It aims to ease the healthcare staff's work, to create a connection of communication at one click between the necessary wards and to reduce the time lost with bureaucratic proceedings. The software (made in PHP programming language, by writing directly in the source code) is developed in order to ease the healthcare staff's activity, being created in a simpler and as elegant way as possible.