• Journal of the Korea Society of Computer and Information
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• v.23 no.7
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• pp.19-26
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• 2018

This paper presents a structuring process of unstructured social network service (SNS) messages on rail services. We crawl messages about rail services posted on SNS and extract keywords indicating date and time, rail operating company, station name, direction, and rail service types from each message. Among them, the rail service types are classified by machine learning according to predefined rail service types, and the rest are extracted by regular expressions. Words are converted into vector representations using Word2Vec and a conventional Convolutional Neural Network (CNN) is used for training and classification. For performance measurement, our experimental results show a comparison with a TF-IDF and Support Vector Machine (SVM) approach. This structured information in the database and can be easily used for services for railway users.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.7
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• pp.1533-1540
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• 2012

u-Life care device collect body bio formation, and classify and store them in exercise patterns. Afterwards, the devices send the data through bluetooth wireless communication to the smart phones which set Google Android operation system at regular intervals. The information is checked out through application. u-Life care device calculates calories spent a day after monitoring activity quantity with 3-axis acceleration sensor. The device judges the status of health through body data mining and consults tailored exercise treatment. When sending body data, the device sends them in smart phone through Blue Tooth wireless communication at once. So, as a strong point, the device doesn't need mobile gateway or home gateway used for sending to web server information sensed from exercise life care products.

• Fourth Industrial Review
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• v.3 no.2
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• pp.11-17
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• 2023

Purpose - Recently, in the field of language education, interest in edutech has increased due to difficulties in classroom teaching due to COVID-19. Accordingly, we would like to analyze research topics related to e-learning before and after COVID-19 and examine the implications for the future Korean language education field. Research design, data, and methodology - This study organized a list of papers to be analyzed by searching for e-learning terms applicable to Korean language education in RISS. The collected data was electronically documented, keywords were extracted using text mining techniques, and word frequencies were checked, and then viewed through cloud visualization. Result - It was confirmed that research on e-learning in the field of Korean language education has increased rapidly in 2021 and 2022. In particular, extensive research on online learning methods has been actively conducted due to the difficulties of face-to-face learning in the COVID-19 era. There have been many studies on teaching and learning methods, such as flipped learning, hybrid learning, blended learning, mobile learning, and smart learning. Conclusion - Since the research so far has mainly focused on online class management methods. Therefore, future research suggests that efforts should be made to develop educational contents and teaching methods using specific ICT technologies. These efforts will contribute to advancing smart education that future education aims for.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.172-174
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• 2021

In the existing industry, maintenance was carried out in the form of preventive maintenance such as occurrence of unnecessary idle time due to limited monitoring and maintenance. However, with the advent of the Fourth Industrial Revolution, real-time monitoring is possible in many industries including mining, manufacturing, oil and gas, and commercial agriculture, and it is desired to minimize idle time due to maintenance. In particular, there is a growing interest in predictive maintenance that can reduce costs and maximize operational efficiency by predicting and maintaining a failure before equipment and equipment fail. In this study, we look at the predictive maintenance technology that can verify the abnormal condition of the equipment of the smart factory in advance and monitor the abnormal condition in real time.

• Journal of Internet Computing and Services
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• v.20 no.3
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• pp.119-128
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• 2019

This study aims to analyze the research trends on Smart City and to present implications to policy maker, industry professional, and researcher. Cities around globe have undergone the rapid progress in urbanization and the consequent dramatic increase in urban dwellings over the past few decades, and faced many urban problems in such areas as transportation, environment and housing. Cities around the globe are in a hurry to introduce Smart City to pursue a common goal of solving these urban problems and improving the quality of their lives. However, various conceptual approaches to smart city are causing uncertainty in setting policy goals and establishing direction for implementation. The study collected 11,527 papers titled "Smart City(cities)" from the Scopus DB and Springer DB, and then analyze research status, topic, trends based on abstracts and publication date(year) information using the LDA based Topic Modeling approaches. Research topics are classified into three categories(Services, Technologies, and User Perspective) and eight regarding topics. Out of eight topics, citizen-driven innovation is the most frequently referred. Additional topic network analysis reveals that data and privacy/security are the most prevailing topics affecting others. This study is expected to helps understand the trends of Smart City researches and predict the future researches.

• Smart Media Journal
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• v.12 no.8
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• pp.9-17
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• 2023

The development of information and communication technology and the improvement of the development and dissemination of smart devices have caused changes in the form of tourism, and the concept of smart tourism has since emerged. In this regard, researches related to smart tourism has been conducted in various fields such as policy implementation and surveys, but there is a lack of research on application reviews. This study collects Trip Advisor application review data in the Google Play Store to identify usage of the application and user satisfaction through Latent Dirichlet Allocation (LDA) topic modeling. The analysis results in four topics, two of which are positive and the other two are negative. We found that users were satisfied with the application's recommendation system, but were dissatisfied when the filters they set during search were not applied or that reviews were not published after updates of the application. We suggest more categories can be added to the application to provide users with different experiences. In addition, it is expected that user satisfaction can be improved by identifying problems within the application, including the filter function, and checking the application environment and resolving the error occurring during the application usage.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.2
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• pp.51-60
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• 2021

Modern society is becoming more informed and intelligent with the development of digital technology, in which humans, objects, and networks relate with each other. In accordance with the changing times, a garden system has emerged that makes it easy to supply the ideal temperature, humidity, sunlight, and moisture conditions to grow plants. Therefore, this study attempted to grasp the concept, perception, and trends of smart gardens, a recent concept. To achieve the purpose of this study, previous studies and text mining were used, and the results are as follows. First, the core characteristics of smart gardens are new gardens in which IoT technology and gardening techniques are fused in indoor and outdoor spaces due to technological developments and changes in people's lifestyles. As technology advances and the importance of the environment increases, smart gardens are becoming a reality due to the need for living spaces where humans and nature can co-exist. With the advent of smart gardens, it will be possible to contribute to gardens' vitalization to deal with changes in garden-related industries and people's lifestyles. Second, in current research related to smart gardens and users' experiences, the technical aspects of smart gardens are the most interesting. People value smart garden functions and technical aspects that enable a safe, comfortable, and convenient life, and subjective uses are emerging depending on individual tastes and the comfort with digital devices. Third, looking at the usage behavior of smart gardens, they are mainly used in indoor spaces, with edible plants are being grown. Due to the growing importance of the environment and concerns about climate change and a possible food crisis, the tendency is to prefer the cultivation of plants related to food, but the expansion of garden functions can satisfying users' needs with various technologies that allow for the growing of flowers. In addition, as users feel the shapes of smart gardens are new and sophisticated, it can be seen that design is an essential factor that helps to satisfy users. Currently, smart gardens are developing in terms of technology. However, the main components of the smart garden are the combination of humans, nature, and technology rather than focusing on growing plants conveniently by simply connecting potted plants and smart devices. It strengthens connectivity with various city services and smart homes. Smart gardens interact with the landscape of the architect's ideas rather than reproducing nature through science and technology. Therefore, it is necessary to have a design that considers the functions of the garden and the needs of users. In addition, by providing citizens indoor and urban parks and public facilities, it is possible to share the functions of communication and gardening among generations targeting those who do not enjoy 'smart' services due to age and bridge the digital device and information gap. Smart gardens have potential as a new landscaping space.

• Journal of Practical Agriculture & Fisheries Research
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• v.20 no.2
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• pp.57-72
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• 2018

In order to extract meaningful information from the excellent farming settlement cases of young farmers published by KNCAF, we studied the key words with text mining and created a word cloud for visualization. First, in the text mining results for the entire sample, the words 'CEO', 'corporate executive', 'think', 'self', 'start', 'mind', and 'effort' are the words with high frequency among the top 50 core words. Their ability to think, judge and push ahead with themselves is a result of showing that they have ability of to be managers or managers. And it is a expression of how they manages to achieve their dream without giving up their dream. The high frequency of words such as "father" and "parent" is due to the high ratio of parents' cooperation and succession. Also 'KNCAF', 'university', 'graduation' and 'study' are the results of their high educational awareness, and 'organic farming' and 'eco-friendly' are the result of the interest in eco-friendly agriculture. In addition, words related to the 6th industry such as 'sales' and 'experience' represent their efforts to revitalize farming and fishing villages. Meanwhile, 'internet', 'blog', 'online', 'SNS', 'ICT', 'composite' and 'smart' were not included in the top 50. However, the fact that these words were extracted without omission shows that young farmers are increasingly interested in the scientificization and high-tech of agriculture and fisheries Next, as a result of grouping the top 50 key words by crop, the words 'facilities' in livestock, vegetables and aquatic crops, the words 'equipment' and 'machine' in food crops were extracted as main words. 'Eco-friendly' and 'organic' appeared in vegetable crops and food crops, and 'organic' appeared in fruit crops. The 'worm' of eco-friendly farming method appeared in the food crops, and the 'certification', which means excellent agricultural and marine products, appeared only in the fishery crops. 'Production', which is related to '6th industry', appeared in all crops, 'processing' and 'distribution' appeared in the fruit crops, and 'experience' appeared in the vegetable crops, food crops and fruit crops. To visualize the extracted words by text mining, we created a word cloud with the entire samples and each crop sample. As a result, we were able to judge the meaning of excellent practices, which are unstructured text, by character size.

• Journal of Korean Society of Transportation
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• v.35 no.5
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• pp.409-422
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• 2017

TOD (Transit-Oriented Development) is one of the urban structure concentrated on the multifunctional space/district with public transportation system, which is introduced for maintaining sustainable future cities. With such trends, the project of building complex transferring centers located at a urban railway station has widely been spreaded and a comprehensive and systematic analytical framework is required to clarify and readily understand the complicated procedure of estimation with the large scale of the project. By doing so, this study is to develop a comprehensive analytical framework for estimating a pedestrian OD matrix using a spatial information and an integrated smart card data, which is so called a data depository and it has been applied to the Samseong station for the model validation. The proposed analytical framework contributes on providing a chance to possibly extend with digitalized and automated data collection technologies and a BigData mining methods.

• The Journal of Bigdata
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• v.3 no.1
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• pp.95-103
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• 2018

In recent years, many people in the manufacturing field have been making efforts to increase efficiency while analyzing manufacturing data generated in the process according to the development of ICT technology. In this study, we propose a data mining based manufacturing process using decision tree algorithm (CHAID) as part of a smart factory. We used 432 sensor data from actual manufacturing plant collected for about 5 months to find out the variables that show a significant difference between the stable process period with low defect rate and the unstable process period with high defect rate. We set the range of the stable value of the variable to determine whether the selected final variable actually has an effect on the defect rate improvement. In addition, we measured the effect of the defect rate improvement by adjusting the process set-point so that the sensor did not deviate from the stable value range in the 14 day process. Through this, we expect to be able to provide empirical guidelines to improve the defect rate by utilizing and analyzing the process sensor data generated in the manufacturing industry.