• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.2
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• pp.397-404
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• 2018

As the usage of internet is increasing, a lot of user behavior are written in a log file and the researches and industries using the log files are getting activated recently. This paper uses the Hadoop based on open source distributed computing platform and proposes a customized tourism system by analyzing user behaviors in the log files. The proposed system uses Google Analytics to get user's log files from the website that users visit, and stores search terms extracted by MapReduce to HDFS. Also it gathers features about the sight-seeing places or cities which travelers want to tour from travel guide websites by Octopus application. It suggests the customized cities by matching the search terms and city features. NBP(next bit permutation) algorithm to rearrange the search terms and city features is used to increase the probability of matching. Some customized cities are suggested by analyzing log files for 39 users to show the performance of the proposed system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.9
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• pp.1144-1151
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• 2021

The pressing process is a compression process in which a product is made by applying force to a heated or unheated material to transform it into the desired shape. Due to the characteristics of press equipment that produces products through continuous compression for a short time, product defects occur continuously, and systems for solving these problems are being developed using various technologies. This paper proposes a real-time defect detection system based on an artificial intelligence algorithm that detects defects. By attaching various sensors to the press device, the relationship between equipment status and defects is defined and collected based on a big data platform. By developing an artificial intelligence algorithm based on the collected data and implementing the developed algorithm using an embedded board, we will show the practicality of the system by applying it to the actual field.

• The Journal of the Korea Contents Association
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• v.18 no.11
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• pp.123-134
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• 2018

Recently, due to the rising incidence of disasters in the nation, there has been a growing interest in the relevance and role of science and technology in solving disaster and safety related issues. In addition, the necessities of securing the human rights of all citizens in disaster risk reduction, identifying fields of technology development for effective disaster response, and improving the efficiency of R&D investment for disaster and safety are becoming more important as the different types of disasters and stages of disaster and safety management process have been considered. In this study, we analyzed bipartite or two-mode networks constructed from an expert survey dataset of technology development for disaster and safety management. The results reveal that earthquake and fire are the two disasters affecting an individual and society at large and demonstrate that AI and big data analytics are effective supports in managing disaster and safety. We believe that such a network analytic approach can be used to explore some important implications exist for the national science and technology effort and successful disaster and safety management practices in Korea.

• The Journal of the Korea Contents Association
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• v.19 no.1
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• pp.74-85
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• 2019

This Study explores the reason why the social media like Cyworld, Iloveschool in Korea in the viewpoint if the layered model by interview. As a result the success factor in the viewpoint of layered model, user used social media for fulfilling the need for linking with other users and the social media offers the customized contents to user. Finally the social media dominated the market in advance. Facebook and Kakao talk are good examples of successful media. The failure factors are to care less about what other users want, to limit the expand of platform and not to copy with the change of the media environment. Iloveschool, Cyworld and Twitter are the examples of failure social media in Korean society. This study highlights the importance of the sensitivity of the change of environment. The expert mentioned the importance of 4th industrial revolution technology like AI, Big data and expected that new technology will emerge and the service will be developed by the change of user's taste.

• Journal of the Korea Safety Management & Science
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• v.22 no.4
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• pp.75-86
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• 2020

With the advent of the 4.0 era of logistics due to the Fourth Industrial Revolution, infrastructures have been built to receive the same services online and offline. Logistics services affected by logistics 4.0 and IT technology are rapidly changing. Logistics services are developing using technologies such as big data, artificial intelligence, blockchain, Internet of things, and augmented reality. The convergence of logistics services and various IT new technologies is accelerating, and the development of data management solution technology has led to the emergence of electronic cargo waybill to replace paper cargo waybill. The electronic waybill was developed to supplement paper waybill that lack economical and safety. However, the electronic waybill that appeared to complement the paper waybill are also in need of complementation in terms of efficiency and reliability. New research is needed to ensure that electronic cargo waybill gain the trust of users and are actively utilized. To solve this problem, electronic cargo waybill that combine blockchain technology are being developed. This study aims to improve the reliability, operational efficiency and safety of blockchain electronic cargo waybill. The purpose of this study is to analyze the blockchain-based electronic cargo waybill system and to derive evaluation indicators for system supplementation.

• Journal of Korean Academic Society of Home Health Care Nursing
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• v.29 no.3
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• pp.278-287
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• 2022

Purpose: To analyze Korean nurse-related channels and video titles on YouTube, the world's largest online video sharing and social media platform, to clarify public opinion and image of nurses. We seek utilization strategies and measures through current status analysis. Methods: Data is collected by crawling video information related to Korean nurses, and correlation is analyzed with frequent word analysis and keyword network analysis. Results: Through the YouTube algorithm, 2,273 videos of 'Nurse' were analyzed in order of recent views, relevance, and rating, and 2,912 videos searched for with the keyword 'Nurse + Hospital, COVID-19, Awareness, University, National Examination' were analyzed. Numerous videos were uploaded, and nursing work that was uploaded in the form of a vlog recorded a high number of views. Conclusion: We could see if the YouTube video shows images of nurses. It has been confirmed that various information is being exchanged rather than information just for promotional purposes.

• Journal of Sensor Science and Technology
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• v.31 no.5
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• pp.318-323
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• 2022

Barium titanate (BaTiO₃) is considered to be a beneficial ceramic material for multilayer ceramic capacitor (MLCC) applications because of its high dielectric constant and low dielectric loss. Numerous attempts have been made to improve the physical properties of BaTiO₃ in response to recent market trends by employing multicomponent alloying strategies. However, owing to its significant number of atomic combinations and unpredictable physical properties, finding a traditional experimental approach to develop multicomponent systems is difficult; the development of such systems is also time-consuming. In this study, 168 new structures were fabricated using special quasi-random structures (SQSs) of Ba_1-xCa_xTi_1-yZryO₃, and 1680 physical properties were extracted from first-principles calculations. In addition, we built an integrated database to manage the computational results, and will provide big data solutions by performing data analysis combined with AI modeling. We believe that our research will enable the global materials market to realize digital transformation through datalization and intelligence of the material development process.

• Journal of Fashion Business
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• v.27 no.3
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• pp.50-62
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• 2023

The e-commerce fashion market has experienced a remarkable growth, leading to an overwhelming availability of shared information and numerous choices for users. In light of this, chatbots have emerged as a promising technological solution to enhance personalized services in this context. This study aimed to develop user-product attributes for a chatbot-based personalized fashion recommendation service using big data text mining techniques. To accomplish this, over one million consumer reviews from Coupang, an e-commerce platform, were collected and analyzed using frequency analyses to identify the upper-level attributes of users and products. Attribute terms were then assigned to each user-product attribute, including user body shape (body proportion, BMI), user needs (functional, expressive, aesthetic), user TPO (time, place, occasion), product design elements (fit, color, material, detail), product size (label, measurement), and product care (laundry, maintenance). The classification of user-product attributes was found to be applicable to the knowledge graph of the Conversational Path Reasoning model. A testing environment was established to evaluate the usefulness of attributes based on real e-commerce users and purchased product information. This study is significant in proposing a new research methodology in the field of Fashion Informatics for constructing the knowledge base of a chatbot based on text mining analysis. The proposed research methodology is expected to enhance fashion technology and improve personalized fashion recommendation service and user experience with a chatbot in the e-commerce market.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.1101-1121
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• 2024

Thorough understanding of user demands and formulation of product development strategies are crucial in product design, and can effectively stimulate consumer behavior. Scientific categorization and classification of demands contribute to accurate design development, design efficiency, and success rates. In recent years, e-commerce has become important consumption platforms for smart wearable products. However, there are few studies on product design and development among those related to promoting platform product services and sales. Meanwhile, design strategies focusing on real consumer needs are scarce among smart wearable product design studies. Therefore, an empirical consumer demand analysis method is proposed and design development strategies are formulated based on a categorized interpretation of demands. Using representative smart bracelets from wearable smart products as a case, this paper classifies consumer demands with three methods: big data semantic analysis, KANO model analysis, and satisfaction analysis. The results reveal that analysis methods proposed herein can effectively classify consumer demands and confirm that differences in consumer demand categories have varying impacts on consumer behavior. On this basis, corresponding design strategies are proposed based on four categories of consumer demands, aiming to make product design the leading factor and promote consumer behavior on e-commerce platforms. This research further enriches demand research on smart wearable products on e-commerce platforms, and optimizes products from a design perspective, thereby promoting consumption. In future research, different data analysis methods will be tried to compare and analyze changes in consumer demands and influencing factors, thus improving research on impact factors of product design in e-commerce.

• Journal of Digital Convergence
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• v.12 no.12
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• pp.313-321
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• 2014

In current society, the digital era that makes enormous amount of data, and the diversified city, the smart space, which has characteristics of creating, collecting and representing data, is appeared. After 2012, in the social media environment called hyper-connected society with wide-spread smart phone, people started to get interested in public data and big data by generalized mobile device and SNS. At first, development of forming platform of data was focused, but now, many different idea from diverse area have been suggested about data analysis and usage to visualize the space intellectualization service. To focus on the visualization process to increase the usage of this public data for ordinary people more than specialized people, this research grasps the present condition of open data and public data service from the current public data portal and considers the applicability of them. As the result of research, the analysis and application of data to ordinary people decrease the use of paper documents, and this research will help to develop the application which is fast and accurate about individual behavior and demand to utilize public data service in intellectual space.