• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.4
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• pp.703-708
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• 2020

The momentum of e-commerce is growing stronger and now, the competition between e-commerce is becoming more and more fierce. In the competition of various e-commerce companies, how to effectively analyze and rationally use these data has become a key point. This paper will use data mining technology to filter out redundant data from large Web databases, extract data that is useful to us, and then analyze them from different perspectives to apply this data reasonably and effectively to our e-commerce website.

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.630-644
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• 2021

Educational data analysis is attracting increasing attention with the rise of the big data industry. The amounts and types of learning data available are increasing steadily, and the information technology required to analyze these data continues to develop. The early identification of potential dropout students is very important; education is important in terms of social movement and social achievement. Here, we analyze educational data and generate predictive models for student dropout using logistic regression, a decision tree, a naïve Bayes method, and a multilayer perceptron. The multilayer perceptron model using independent variables selected via the variance analysis showed better performance than the other models. In addition, we experimentally found that not only grades but also extracurricular activities were important in terms of preventing student dropout.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.3
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• pp.479-491
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• 2024

Android manufacturers collect diagnostic data to improve the quality of service to users around the world. The content and frequency of diagnostic data collected by these Android manufacturers is unknown. We analyze the diagnostic data collection behavior of Samsung smartphones, which has the largest share of the Android market among smartphone manufacturers, to explain which diagnostic data is communicated to the server via network packets, how the system app that collects the diagnostic data works, and whether the diagnostic data violates user privacy.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.5
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• pp.961-966
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• 2012

In this paper, we analyze a main patent positioning to analyze data based on patent application as stage of data collection to organize knowledge map of LED through patent application. We also analyze the present condition of patent application for technology sector. We propose basic data to make knowledge map through the analysis of technical distribution for applicant by each country.

• Journal of Digital Convergence
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• v.13 no.10
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• pp.1-7
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• 2015

Many people are interesting software quality. Because of, we depend on software in our life. In terms of, I think, good software is a good quality software. So, when we develop the software, we need trying to improve software quality. In this paper, we analyze software test data. We emphasize that software quality is very important in our life. We use software experimental data, in order to analyze of software quality. On the basis of ISO/IEC 9126-2, we classify the test data and we analyze the difference of error frequency according to functionality, reliability, usability, efficiency, maintainability, portability. We analyze the number of test and used time according software type. We want to search effect variable, going through testing result and measurement convergence, we know the effect variable of functionality and efficiency.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.25 no.5
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• pp.46-52
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• 2002

Today's database system needs to collect huge amount of questionnaire that results from development of the information technology by the internet, so it has to be administrable. However, there are many difficulties concerned with finding analytic data or useful information in the high capacity-database. Data mining can solve these problems and utilize the database. Questionnaire analysis that uses data mining has drawn relevant patterns that did not look or was tended to overlook before. These patterns can be applied by a new business rule. The purpose of this research is to analyze the questionnaire results and to present the result that can help to make decision easily with data mining. Recognition and analysis about these techniques of data mining show suitable type of questionnaire survey. This research focus on the form of present composition and the model of suitable questionnaire to analyze the type of it. Also, the comparison between the actual questionnaire result and the conventional statistical analysis is examined.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1999.10c
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• pp.175-180
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• 1999

The purpose of this study is to investigate on tideland recalamation project as a part of situation on farm land improvement measures in North Korea. By using satelite image data beyond the national boundaries, it makes possbile to analyze tideland reclamation projects, and owing to the developed software and procedure we can analyze data regardless of difference in data acquistion date. Satellite image data LANDSAT JEARS-1 data are mainly used, and analyzing software ER Mapper, ERDAS , IDRISI are used . Reclamation survey result made by the ministry of unification in 1994 were examined by means of remote sensing using satellite image data. The results are ; Completed and/or partly completed project are 24, 596ha and planned are about 142, 223 ha, 166, 819 ha in total. However, they already reported about 300 thousand ha would be reclamined from the sea in early 1980.

• Journal of Information Processing Systems
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• v.14 no.1
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• pp.140-149
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• 2018

Social data such as users' comments are unstructured in nature and up-to-date technologies for analyzing such data are constrained by the available storage space and processing time when fast storing and processing is required. On the other hand, it is even difficult in using a huge amount of dynamically generated social data to analyze the user features in a high speed. To solve this problem, we design and implement a topic association analysis system based on the latent Dirichlet allocation (LDA) model. The LDA does not require the training process and thus can analyze the social users' hourly interests on different topics in an easy way. The proposed system is constructed based on the Spark framework that is located on top of Hadoop cluster. It is advantageous of high-speed processing owing to that minimized access to hard disk is required and all the intermediately generated data are processed in the main memory. In the performance evaluation, it requires about 5 hours to analyze the topics for about 1 TB test social data (SNS comments). Moreover, through analyzing the association among topics, we can track the hourly change of social users' interests on different topics.

• Journal of Information Technology Services
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• v.22 no.3
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• pp.29-47
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• 2023

With the recent advancement of information and communication technologies such as artificial intelligence, big data, cloud computing, and 5G, data is being produced and digitized in unprecedented amounts. As a result, data has emerged as a critical resource for the future economy, and overseas countries have been revising laws for data protection and utilization. In Korea, the 'Data 3 Act' was revised in 2020 to introduce institutional measures that classify personal information, pseudonymized information, and anonymous information for research, statistics, and preservation of public records. Among them, it is expected to increase the added value of data by combining pseudonymized personal information, and to this end, "the Expert Data Combination Agency" and "the Expert Data Agency" (hereinafter referred to as the Expert Data Processing Agency) system were introduced. In comparison to these domestic systems, we would like to analyze similar overseas systems, and it was recently confirmed that the Vermont government in the United States enacted the first "Data Broker Act" in the United States as a measure to protect personal information held by data brokers. In this study, we aim to compare and analyze the roles and functions of the "Expert Data Processing Agency" and "Data Broker," and to identify differences in designated standards, security measures, etc., in order to present ways to contribute to the activation of the data economy and enhance information protection.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.23 no.3
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• pp.201-209
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• 2017

The Big Data, the element of the Fourth Industrial Revolution, is drawing attention as the 4th Industrial Revolution is mentioned in the 2016 World Economic Forum. Big Data is being used in various fields because it predicts the near future and can create new business. However, utilization and research in the field of packaging are lacking. Today packaging has been demanded marketing elements that effect on consumer choice. Big data is actively used in marketing. In the marketing field, big data can be used to analyze sales information and consumer reactions to produce meaningful results. Therefore, this study proposed a method of applying big data in the field of packaging focusing on marketing. In this study suggest that try to utilize the private data and community data to analyze interaction between consumers and products. Using social big data will enable to understand the preferred packaging and consumer perceptions and emotions in the same product line. It can also be used to analyze the effects of packaging among various components of the product. Packaging is one of the many components of the product. Therefore, it is not easy to understand the impact of a single packaging element. However, this study presents the possibility of using Big Data to analyze the perceptions and feelings of consumers about packaging.