• The KIPS Transactions:PartB
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• v.8B no.6
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• pp.609-616
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• 2001

Today, as the Internet is popularized, information and news retrieval are generalized. However due to the tremendous amount and variety of information, many users appeal the difficulties of information retrieval. Thus in this paper, we propose a news retrieval system, which filters news articles using an intelligent agent with the learning ability of BPN (back propagation neural network). This system also uses a profile to accomodate the personalized news retrieval. This system consists of two major agents, collection agent and learning agent. The collection agent gathers the articles from several news sites, analyzes them, and stores into a database. The learning agent builds the BPN based on the personalized data. In addition, considering the popularity of the wireless internet due to the rapid development of communication technologies, we made this system provide the service through the wireless internet.

• Journal of Digital Convergence
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• v.13 no.9
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• pp.269-276
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• 2015

Recently, with the activation of the industry related to the big data, the global security companies have expanded their scopes from structured to unstructured data for the intelligent security threat monitoring and prevention, and they show the trend to utilize the technique of user's tendency analysis for security prevention. This is because the information scope that can be deducted from the existing structured data(Quantify existing available data) analysis is limited. This study is to utilize the analysis of security tendency(Items classified purpose distinction, positive, negative judgment, key analysis of keyword relevance) applying the machine learning algorithm($Na{\ddot{i}}ve$ Bayes, Decision Tree, K-nearest neighbor, Apriori) in the big data environment. Upon the capability analysis, it was confirmed that the security items and specific indexes for the decision of security tendency could be extracted from structured and unstructured data.

• The KIPS Transactions:PartB
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• v.15B no.3
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• pp.211-218
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• 2008

In this paper, we proposed a new image summarization algorithm designed for automatically summarizing user's snapshot photos taken in a virtual environment based on user's context information and educational contents, and then presenting a summarized photos shortly after user's virtual reality experience. While other image summarization algorithms used date, location, and keyword to effectively summarize a large amount of photos, this algorithm is intended to improve users' memory retention by recalling their interests and important educational contents. This paper first describes some criteria of extracting the meaningful images to improve learning effects and the identification rate calculations, followed by the system architecture that integrates the virtual environment and the viewer interface. It will also discuss a user study to model the algorithm's optimal identification rate and then future research directions.

• Journal of the Korea Convergence Society
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• v.9 no.12
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• pp.25-32
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• 2018

In the massive online fashion market, it is not easy for consumers to find the fashion style they want by keyword search for their preferred style. It can be resolved into consumer needs based fashion recommendation. Most of the existing online shopping sites have collected cumtomer's preference style using the online quastionnair. In this paper, we propose a simple but effective novel model that resolve the traditional method in fashion profiling for consumer's preference style and needs using implicit profiling method. In addition, we proposed a learning model that reflects the characteristics of the images itself through the deep learning-based intelligent preferred fashion model learned from the collected data. We show that the proposed model gave meaningful results through the qualitative evaluation.

• Journal of Korean Home Economics Education Association
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• v.36 no.2
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• pp.33-50
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• 2024

This study examined the trends in home economics education research across different curriculum periods and journals. A total of 374 papers related to the 2009, 2015, and 2022 revised curricula were selected and analyzed using network analysis from four journals. First, research trends were analyzed by curriculum period. Keyword frequency analysis revealed that articles on the 2009 and 2015 revised curricula primarily focused on analyzing the curriculum to develop textbooks or programs. In contrast, papers on the 2022 revised curriculum explored broader directions. Topic modeling results highlighted the prominent topics for each period: 'environmental education' in the 2009 revised curriculum, 'safety and health education' in the 2015 revised curriculum, and 'ecological transition' in the 2022 revised curriculum. Second, research trends were analyzed by journal. Keyword frequency analysis by journal exposed specific research tendencies. For example, in the Journal of Home Economics Research, 'perceptions of practical classes' and 'analysis of safety textbooks' were major topics for the 2009 revised curriculum, while 'teaching and learning plans for competence development' dominated research on the 2015 revised curriculum. This study demonstrates that the concepts and goals emphasized in curriculum revisions are reflected in the corresponding research.

• Journal of Korean Library and Information Science Society
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• v.51 no.2
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• pp.1-21
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• 2020

The purpose of this study is to explore semantic characteristics of IFLA school library guidelines through network analysis. There are two versions, 2002 edition and 2015 revision of the guidelines. This study analyzed the 2002 edition and 2015 revision of the IFLA school library guidelines view point of semantic network, and compared characteristics of two versions. The keywords were to extracted from two texts, semantic network were composed based on co-occurrence relations with keywords. The centrality(degree centrality, closeness centrality, betweenness centrality) was analyzed from the network. In addition, this study conducted topic modeling analysis using LDA function of NetMiner4.0. The result of this study is following these. First, When comparing the centrality, the 'Program, Teaching, Reading, Inquiry, Literacy, Media' keyword was higher in the 2015 revision than in the 2002 edition. Second, 'Inquiry' in degree centrality and 'Achievement' in closeness centrality which were not included in the 2002 edition top-ranked keyword list, have new appeared in 2015 revision. third, As a result of the analysis of topic modeling, compared to the 2002 version, the importance of topics on programs and services, teaching and learning activities of librarian teacher, and media and information literacy is increasing in the 2015 revision.

• The Journal of the Korea Contents Association
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• v.8 no.11
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• pp.412-425
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• 2008

One of the important elements for improving academic achievement of learners in education through e-learning is to support learners to study by finding questions they want with providing various evaluation questions. However, most of question retrieval systems usually depend on keyword search based on only a syntactical analysis and/or a hierarchical browsing system classified by the topics of subjects. In such a system it is not easy to find integrative questions associated with each other. In order to improve this problem, in this paper we proposed a question management and retrieval system which allows users to easily manage questions and also to effectively find questions for study on the Web. Then, we implemented a system that gives to access questions for the domain of C language programming. The system makes it possible to easily search questions related to not only a single theme but also questions integrated by interrelationship between topics and questions. This is done by supporting to be able to retrieve questions according to conceptual interrelationships between questions from user query. Consequently, it is expected that the proposed system will provide learners to understand the basic theories and the concepts of the subjects as well as to improve the ability of comprehensive knowledge utilization and problem-solving.

• Journal of The Korean Association of Information Education
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• v.20 no.6
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• pp.563-574
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• 2016

This paper is a research on the curriculums of network and digital creation tools among SW education in order to apply them to SW curriculum in education fields. For doing so, a curriculum model was developed by extracting main key words through the analyses of domestic and foreign SW curriculum, and reorganization of concept understanding and learning activity elements was made so as to be fit to characteristics of each curriculum. And curriculums were remodeled by curriculum such like concept understanding was focussed in network, activities in digital creation tools and its validity was suggested through expert verification by composing contents elements based on the results. Also, this model was proposed so that each school could recompose it easily by combining contents elements of other curriculums. Therefore, the suggested model could be utilized as a basic research data in applying domestic SW curriculum standard model.

• Journal of KIISE
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• v.41 no.12
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• pp.1110-1116
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• 2014

Nowadays, social networking sites (SNSs), such as Twitter, LinkedIn, and Tumblr, are coming into the forefront, due to the growth in the number of users. While users voluntarily provide their information in SNSs, privacy leakages resulting from the use of SNSs is becoming a problem owing to the evolution of large data processing techniques and the raising awareness of privacy. In order to solve this problem, the studies on protecting privacy on SNSs, based on graph and machine learning, have been conducted. However, examples of privacy leakages resulting from the advent of a new SNS are consistently being uncovered. In this paper, we propose a technique enabling a user to detect privacy leakages beforehand in the case where the service provider or third-party application developer threatens the SNS user's privacy maliciously.

• The Journal of the Korea Contents Association
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• v.14 no.8
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• pp.517-527
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• 2014

Universities are increasing every year, supporting the university's teaching and learning center, among subjects which recently retake a good teaching or the most memorable teaching through an essay competitions. This contributed to the development of students' academic skills taught a good teaching know-how to identify and spread the 'good teaching' what has provided opportunity to look back. This study analyzed the characteristics of good teaching, as perceived by Junior College students. We did content analysis to elicit the characteristics of professor from qualitative comments of 75 college essay competitions. According to the content analysis, the most essential characteristics of good teaching as perceived by Junior College students are the following: 1. the professor's enthusiasm for teaching; 2. students' interest for teaching; 3. providing clear explanation; 4. caring professors; 5. good communication with students; 6. sharing professor's experiences.