• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.4
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• pp.163-180
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• 2022

Real estate data can be big data. Because the amount of real estate data is growing rapidly and real estate data interacts with various fields such as the economy, law, and crowd psychology, yet is structured with complex data layers. The existing Relational Database tends to show difficulty in handling various relationships for managing real estate big data, because it has a fixed schema and is only vertically extendable. In order to improve such limitations, this study constructs the real estate data in a Graph Database and verifies its usefulness. For the research method, we modeled various real estate data on MySQL, one of the most widely used Relational Databases, and Neo4j, one of the most widely used Graph Databases. Then, we collected real estate questions used in real life and selected 9 different questions to compare the query times on each Database. As a result, Neo4j showed constant performance even in queries with multiple JOIN statements with inferences to various relationships, whereas MySQL showed a rapid increase in its performance. According to this result, we have found out that a Graph Database such as Neo4j is more efficient for real estate big data with various relationships. We expect to use the real estate Graph Database in predicting real estate price factors and inquiring AI speakers for real estate.

• International Journal of Computer Science & Network Security
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• v.21 no.2
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• pp.188-192
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• 2021

In this paper, we apply data mining techniques and machine learning algorithms using R software, which is used to predict, here we applied a regression model to test some factor on the dataset for which we assumed that it effects student performance. Model was built on an existing dataset which contains many factors and the final grades. The factors tested are the attention to higher education, absences, study time, parent's education level, parent's jobs, and the number of failures in the past. The result shows that only study time and absences can affect the students' performance. Prediction of student academic performance helps instructors develop a good understanding of how well or how poorly the students in their classes will perform, so instructors can take proactive measures to improve student learning. This paper also focuses on how the prediction algorithm can be used to identify the most important attributes in a student's data.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.4
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• pp.292-299
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• 2021

A form of data mining software, based on manufacturing-based IIoT environment with the development of IT technologies are increasingly growing. However, it is difficult to evaluate the software quality in the same form as general software due to the characteristics of the software of a manufacturing company that has a large amount of data that needs to be carried out with big data and data mining. In addition, in a manufacturing-based environment where heterogeneous equipment and software are mixed, it is difficult to perform quality judgment on software used by applying existing quality characteristics. Therefore, in this paper, the characteristics of the manufacturing base are investigated, and a software quality evaluation model suitable for it is developed and evaluated.

• International Journal of Computer Science & Network Security
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• v.24 no.7
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• pp.177-185
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• 2024

Web science, a general discipline of learning is presently at high demand of expertise with ideas to develop software-based WebApps and MobileApps to facilitate user or customer demand e.g. shopping etc. electronically with the access at their smartphones benefitting the business enterprise as well. A worldwide-computerized reservation network is used as a single point of access for reserving airline seats, hotel rooms, rental cars, and other travel related items directly or via web-based travel agents or via online reservation sites with the advent of social-web, e-commerce, e-business, from anywhere-on-earth (AoE). This results in the accumulation of large and diverse distributed databases known as big data. This paper describes a novel intelligent web-based electronic booking framework for e-business with distributed computing and data mining support with the detail of e-business system flow for e-Booking application architecture design using the approaches for distributed computing and data mining tools support. Further, the importance of business intelligence and data analytics with issues and challenges are also discussed.

• Journal of Distribution Science
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• v.21 no.3
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• pp.25-36
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• 2023

Purpose: Brand community in higher education institutions comes up as an important topic to be discussed because the relationships among consumers can support the institutional brand and ultimately give meaning and vitality to the market-oriented strategy. This study aims to investigate how the literature on brand community in higher education have been distributed in research trends, theoretical frameworks, and methods. Research design, data and methodology: A total of 24 articles were organized from four reputable international databases. Content analysis were performed followed by synthesis toward potential directions and suggestions. Results: The researches in this area have increasingly focused on online interaction. Social identity theory and relationship theory were the two most prevalent theories used. Since the internet provides any social relationship with a specific relationship to form the brand community, its contextualization in higher education resulted in new concept implementation. Conclusions: The relationship within online participati on has impacted the market-oriented strategy of higher education in searching for ways toward a long-term and enduring bond among students, alumni, institutions and brands. As there is a plenteous prospect of data availability combined with big data analysis technology, the online participation will pique the interest of scholars to conduct further research on it.

• Journal of Engineering Education Research
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• v.27 no.4
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• pp.3-11
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• 2024

This study classified domestic and international systems by type, presenting their key features and examples, with the aim of outlining future directions for system development and research. AI-based learning assistance systems can be categorized into instructional-learning evaluation types and academic recommendation types, depending on their purpose. Instructional-learning evaluation types measure learners' levels through initial diagnostic assessments, provide customized learning, and offer adaptive feedback visualized based on learners' misconceptions identified through learning data. Academic recommendation types provide personalized academic pathways and a variety of information and functions to assist with overall school life, based on the big data held by schools. Based on these characteristics, future system development should clearly define the development purpose from the planning stage, considering data ethics and stability, and should not only approach from a technological perspective but also sufficiently reflect educational contexts.

• Journal of Practical Engineering Education
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• v.15 no.2
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• pp.401-408
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• 2023

In this study, a career exploration program was developed for athletic students. Therefore, existing research on career exploration for athletics was analyzed, requirements were identified, and a learning plan was designed. Based on this, a step-by-step educational program was developed. In addition, since research on career exploration for athletic students was not active in previous studies, 'problem definition' - 'data collection' - 'data preprocessing' - 'data analysis' by referring to existing career exploration studies that were studied in the school field. - 'Data visualization' - 'Simulation analysis' were divided into stages to conduct the study. Through this study, it is expected that research on vocational education for athletic students will be more active.

• International journal of advanced smart convergence
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• v.11 no.3
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• pp.79-84
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• 2022

Due to a series of online sex crimes cases and online class conversions caused by the spread of the coronavirus, alternatives to sex education in schools are urgently required. As a result of this study, the metaverse sex education platform was designed. Using this platform, learners are expected to cultivate correct adult awareness and digital citizenship. Within the metaverse platform, learners can participate more actively in learning. Instead of exposing one's name and face in a place dealing with sensitive gender issues, one can participate in education through his or her decorated avatar and participate in education much more actively than face-to-face education and express one's opinion through chat. In addition, education by level can be received regardless of time and place, which can have the effect of bridging the educational gap between urban and rural areas. In this paper, we propose a new sex education platform without time and space constraints by utilizing metaverse.

• Korean Journal of Childcare and Education
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• v.11 no.6
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• pp.177-198
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• 2015

This study is aimed at a comparison analyzing the contents of child 'safety education' in Three-four-year-old Nuri curriculum manual for teachers related activity type and activity form, life theme based on the criteria of analysis. First, the number of contents of child 'safety education' included in the 3 year old Nuri curriculum manual for teachers was 136, and among them, 71(52.2%) were from in big and small group activity. Total 124 contents were in 4-year old group and showed 58(46.8%) contents in big and small group activity. Second, it was identified that the Three-four-year-old Nuri curriculum handled highest number of child 'safety education' activities. Twenty-five activities from 'appliances' among a total of 127 child 'safety education' activities were included and included 21 activities in contents of 'safety for object, tool, and apparatus.' Thirty-three activities among 'health and safety' among a total of 131 child 'safety education' activities were included and it was identified that the highest number of child 'safety education' activities were conducted in 'safety for disease' contents. It will be hope to suggest some of the providing child 'safety education' of Three-four-year-old in education field, and to provide basic data for planning and suggesting directions for various training related to child safety education. Moreover, this study intends to provide basic data for composing necessary manual and program for child 'safety education' and to provide basic data for expanding the safety experience facility.

• Journal of The Korean Association of Information Education
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• v.26 no.1
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• pp.45-53
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• 2022

The need for artificial intelligence education has emerged, and countries around the world are announcing artificial intelligence strategies. Artificial intelligence education is reflected in the main points of the 2022 revised curriculum general published in Korea. Along with this interest, programs related to artificial intelligence education are being developed, but it is difficult to find artificial intelligence programs for lower grades of elementary school. This study aims to develop a data collection education program for the lower grades of elementary school through a series of analysis-design-development-application-evaluation processes and apply it to first-grade elementary school students to verify its effectiveness. Through the developed program, it is expected that students will be able to understand and feel interested in artificial intelligence, and develop an attitude of collecting data in their daily lives through the process of searching for various types of data in their daily lives.