• KIPS Transactions on Software and Data Engineering
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• v.5 no.6
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• pp.295-306
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• 2016

The purpose of this paper is both to analyze research trends and to predict industrial flows using the meta-data from the previous studies on data quality. There have been many attempts to analyze the research trends in various fields till lately. However, analysis of previous studies on data quality has produced poor results because of its vast scope and data. Therefore, in this paper, we used a text mining, social network analysis for time series network analysis to analyze the vast scope and data of data quality collected from a Web of Science index database of papers published in the international data quality-field journals for 10 years. The analysis results are as follows: Decreases in Mathematical & Computational Biology, Chemistry, Health Care Sciences & Services, Biochemistry & Molecular Biology, Biochemistry & Molecular Biology, and Medical Information Science. Increases, on the contrary, in Environmental Sciences, Water Resources, Geology, and Instruments & Instrumentation. In addition, the social network analysis results show that the subjects which have the high centrality are analysis, algorithm, and network, and also, image, model, sensor, and optimization are increasing subjects in the data quality field. Furthermore, the industrial connection analysis result on data quality shows that there is high correlation between technique, industry, health, infrastructure, and customer service. And it predicted that the Environmental Sciences, Biotechnology, and Health Industry will be continuously developed. This paper will be useful for people, not only who are in the data quality industry field, but also the researchers who analyze research patterns and find out the industry connection on data quality.

• Journal of the Korean Society for information Management
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• v.38 no.3
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• pp.73-99
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• 2021

The purpose of this study is to analyze the health information use experience of middle-aged people in their 40s and 50s and to observe and analyze their health information search behaviors according to health consciousness and health information orientation. This study uses Information Foraging Theory with the concept of information scents which leads users to detect and collect cues in information searching. Types and contents of information cues that middle-aged people use when searching for health information were investigated. Also, how their health consciousness and health information orientation affected using information cues were analyzed. Three methods of research were used; (1) pre-interviews, (2) search experiments, and (3) post-interviews. Thirty-two middle-aged people participated in the study. Their performance on health information searching was recorded and referred to in the post-interviews using a think-aloud protocol. Findings presented that middle-aged people's health consciousness and health information orientation affected the perception of information scents in health information search; those with high health consciousness and health information orientation consider the text made by the government office the most critical information cues. We believe findings from this study could be used for public libraries or non-profit institutions to understand middle-aged people's health information behaviors to design education programs for information retrieval considering users' health consciousness and health information orientation. Findings could also contribute to Internet portal site or health-related web site designers developing strategies for middle-aged users to access health information effectively.

• Korean small business review
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• v.43 no.4
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• pp.27-57
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• 2021

How does authenticity influence the process that conducts a company's CSR Strategy? Authenticity, an internal/external alignment condition that an employee feels in relation to an organization, means the decision on how true and beneficial to employees through their experiences, such as thoughts and emotions. Also, it can be understood as a process of meaning formation between the organization's strategy to conduct CSR and the perception of employees conducting CSR. To prove the relation between authenticity and CSR clearly, we used various techniques like Text Mining, Topic Modeling and Semantic network analysis about O corporation's 657 review data, from 2015 to 2021. As a result of the analysis, we find out the special issues and types. The analysis shows that the issue concerning the 'external image' is the biggest characteristic of authenticity perception in other conditions. Furthermore, the types of authenticity perception evaluations are largely divided into acceptance and rejection, in detail, five categories. This study indicates that organizations should consider both external and internal conditions when establishing CSR strategies. In addition, it is necessary to be an interactive circular relationship between the organization and employee, collecting and reflecting employee's perceptions. Finally, this study proposes ways to overcome problems related to interaction.

• Journal of Korean Home Economics Education Association
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• v.34 no.1
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• pp.1-16
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• 2022

This study was performed to develop educational materials in the form of card news that can be easily accessed on mobile phones or the Internet for milk intake education of the elderly based on the scientific evidence and their needs. The themes included in the card news were selected based on the literature and focus group interviews with 10 elderly individuals (78.10±6.66 years old). For the selected themes, information that elderly users most want to know was selected for the purpose of effective communication, while reflecting the eating habits, lifestyle, living environment, and nutrition and health status of the elderly in Korea. The draft of the card news was reviewed by the researcher, consulted by experts, and surveyed with 50 elderly individuals (70.44±5.16 years old). Based on the results of the review, consultations, and the survey, a final draft of the card news consisting of 12 pages was completed. The card news of the present study is expected to be an effective educational material considering the high level of satisfaction (higher than 4 on the 5-point scales) indicated by the survey respondents. Therefore this card news is expected to help increase milk intake through friendly milk education for the elderly.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.185-207
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• 2022

Recently, with the development of deep learning technology, researches to apply a deep learning algorithm to analyze unstructured data such as text and images are being actively conducted. Text classification has been studied for a long time in academia and industry, and various attempts are being performed to utilize data characteristics to improve classification performance. In particular, a hierarchical relationship of labels has been utilized for hierarchical classification. However, the top-down approach mainly used for hierarchical classification has a limitation that misclassification at a higher level blocks the opportunity for correct classification at a lower level. Therefore, in this study, we propose a methodology for classifying hierarchical data using the autoencoder-based deeply supervised network that high-level classification does not block the low-level classification while considering the hierarchical relationship of labels. The proposed methodology adds a main classifier that predicts a low-level label to the autoencoder's latent variable and an auxiliary classifier that predicts a high-level label to the hidden layer of the autoencoder. As a result of experiments on 22,512 academic papers to evaluate the performance of the proposed methodology, it was confirmed that the proposed model showed superior classification accuracy and F1-score compared to the traditional supervised autoencoder and DNN model.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.189-198
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• 2023

As crimes frequently occur on the street, the spread of CCTV is increasing. However, due to the shortcomings of passively operated CCTV, the need for intelligent CCTV is attracting attention. Due to the heavy system of such intelligent CCTV, high-performance devices are required, which has a problem in that it is expensive to replace the general CCTV. To solve this problem, an intelligent CCTV system that recognizes low-quality images and operates even on devices with low performance is required. Therefore, this paper proposes a Saying CCTV system that can detect threats in real time by using the AWS cloud platform to lighten the system and convert images into text. Based on the data extracted using YOLO v4 and OpenPose, it is implemented to determine the risk object, threat behavior, and threat situation, and calculate the risk using machine learning. Through this, the system can be operated anytime and anywhere as long as the network is connected, and the system can be used even with devices with minimal performance for video shooting and image upload. Furthermore, it is possible to quickly prevent crime by automating meaningful statistics on crime by analyzing the video and using the data stored as text.

• Information Systems Review
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• v.22 no.2
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• pp.167-199
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• 2020

The ICT-based curation as a series of experiences with the mobile exhibition-guide applications or guide programs in art galleries helps visitors fully immersed in the exhibition and allows them to have more informative and convenient guide experience at art galleries. This study aims to verify how the factors of ICT-based curation affects the commitment and satisfaction of visitors at art galleries, figure out whether the visitors' commitment has effects on their satisfaction, and then finally test the impact of their commitment and satisfaction on their revisit intention. In order to validate the cause-and-effect relationships between these factors, the ICT-based curation in this paper is categorized into five factors - gamification, quality of image/video information, quality of sound/text information, contextual offer, and instant connectivity. The main results of the study are as follows. First, only the gamification has significantly positive effects on the commitment of art gallery visitors, while other two factors - the instant connectivity, and the quality of sound/text information - have significantly positive effects on the satisfaction of visitors. Second, the commitment of visitors also has significantly positive effects on their satisfaction. Third, the commitment of the visitors don't have significantly positive relationship with their intention of revisit, but the satisfaction of the visitors have significantly positive relationship with their intention of revisit.

• The Journal of Bigdata
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• v.4 no.2
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• pp.1-12
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• 2019

As Artificial Intelligence (AI) technology develops, it is applied to various fields such as image, voice, and text. AI has shown fine results in certain areas. Researchers have tried to predict the stock market by utilizing artificial intelligence as well. Predicting the stock market is known as one of the difficult problems since the stock market is affected by various factors such as economy and politics. In the field of AI, there are attempts to predict the ups and downs of stock price by studying stock price patterns using various machine learning techniques. This study suggest a way of predicting stock price patterns based on the Convolutional Neural Network(CNN) among machine learning techniques. CNN uses neural networks to classify images by extracting features from images through convolutional layers. Therefore, this study tries to classify candlestick images made by stock data in order to predict patterns. This study has two objectives. The first one referred as Case 1 is to predict the patterns with the images made by the same-day stock price data. The second one referred as Case 2 is to predict the next day stock price patterns with the images produced by the daily stock price data. In Case 1, data augmentation methods - random modification and Gaussian noise - are applied to generate more training data, and the generated images are put into the model to fit. Given that deep learning requires a large amount of data, this study suggests a method of data augmentation for candlestick images. Also, this study compares the accuracies of the images with Gaussian noise and different classification problems. All data in this study is collected through OpenAPI provided by DaiShin Securities. Case 1 has five different labels depending on patterns. The patterns are up with up closing, up with down closing, down with up closing, down with down closing, and staying. The images in Case 1 are created by removing the last candle(-1candle), the last two candles(-2candles), and the last three candles(-3candles) from 60 minutes, 30 minutes, 10 minutes, and 5 minutes candle charts. 60 minutes candle chart means one candle in the image has 60 minutes of information containing an open price, high price, low price, close price. Case 2 has two labels that are up and down. This study for Case 2 has generated for 60 minutes, 30 minutes, 10 minutes, and 5minutes candle charts without removing any candle. Considering the stock data, moving the candles in the images is suggested, instead of existing data augmentation techniques. How much the candles are moved is defined as the modified value. The average difference of closing prices between candles was 0.0029. Therefore, in this study, 0.003, 0.002, 0.001, 0.00025 are used for the modified value. The number of images was doubled after data augmentation. When it comes to Gaussian Noise, the mean value was 0, and the value of variance was 0.01. For both Case 1 and Case 2, the model is based on VGG-Net16 that has 16 layers. As a result, 10 minutes -1candle showed the best accuracy among 60 minutes, 30 minutes, 10 minutes, 5minutes candle charts. Thus, 10 minutes images were utilized for the rest of the experiment in Case 1. The three candles removed from the images were selected for data augmentation and application of Gaussian noise. 10 minutes -3candle resulted in 79.72% accuracy. The accuracy of the images with 0.00025 modified value and 100% changed candles was 79.92%. Applying Gaussian noise helped the accuracy to be 80.98%. According to the outcomes of Case 2, 60minutes candle charts could predict patterns of tomorrow by 82.60%. To sum up, this study is expected to contribute to further studies on the prediction of stock price patterns using images. This research provides a possible method for data augmentation of stock data.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.5
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• pp.183-189
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• 2009

Recently, PCS, PDA and mobile devices, such as the proliferation of spread, GPS (Global Positioning System) the use of, the rapid development of wireless network and a regular user even images, audio, video, multimedia data, such as increased use is for. In particular, video data among multimedia data, unlike the moving object, text or image data that contains information about the movements and changes in the space of time, depending on the kinds of changes that have sigongganjeok attributes. Spatial location of objects on the flow of time, changing according to the moving object (Moving Object) of the continuous movement trajectory of the meeting is called, from the user from the database that contains a given query trajectory and data trajectory similar to the finding of similar trajectory Search (Similar Sub-trajectory Retrieval) is called. To search for the trajectory, and these variations, and given the similar trajectory of the user query (Tolerance) in the search for a similar trajectory to approximate data matching (Approximate Matching) should be available. In addition, a large multimedia data from the database that you only want to be able to find a faster time-effective ways to search different from the existing research is required. To this end, in this paper effectively divided into a grid to search for the trajectory to the trajectory of moving objects, similar to the effective support of the search trajectory offers a new grid-based search techniques.

• Journal of Digital Convergence
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• v.11 no.8
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• pp.65-73
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• 2013

Outcome of election depends on which candidate of politics uses more original and creative idea for Ads and PR of election in election campaign strategy of political campaign. Especially, since political Ads and PR are the ways of capturing voters' sensitivities with one line of copy(slogan) and one image, Ads and PR are very important. This research analyzes unique and creative trend of political campaigns which are used in each unit election which is held four times(2010. 6 2 local election, 2011. 10 26 by-election, 2012. 4 11 general election, 2012. 12 19 presidential election) during 2010~2012. For analysis, search analysis of text and image used in video, internet, booklet type of Ads and PR material for election, and election campaign. Video is used in election campaign during election period. Unique and creative political campaign is customized micro-marketing election strategy trend which tries to fit for tendency of backing including gender, age group, social atmosphere, etc. This research excludes the degree of success of this election strategy from subject of analysis.