• The Journal of the Korea Contents Association
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• v.21 no.10
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• pp.21-37
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• 2021

This study investigated the intellectual structure of the latest trends in Korean addiction research in the social sciences. A network analysis of keywords with co-word occurrence was performed on 172 papers from the KCI database based on the data from the year of 2019, and a total of 432 keywords were extracted. The network analysis was performed using several programs: Bibexcel, COOC, WNET, and NodeXL. As a result of the study, keywords related to addiction type, study subjects, research methods, and research variables were found, and a total of 20 clusters were identified. Furthermore, to identify and measure weighted networks, the relationships between each keyword were explored and discussed in detail through a network analysis of global centralities, local centralities, and betweenness centralities. The study indicated that the latest issues were focused on smartphone addiction and provided implications for the future research and practice that fields and topics of relationship addiction, food addiction, and work addiction should be more considered. Further, the study discussed the relationship between drug addiction-crime, alcohol addiction-family, and gambling addiction-motivation and the necessity of qualitative study.

• Journal of dental hygiene science
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• v.21 no.2
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• pp.104-110
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• 2021

Background: Regardless of countries, the myth that rain makes the body ache has been worded in various forms, and a number of studies have been reported to investigate this. However, these studies, which depended on the patient's experience or memory, had obvious limitations. Google Trends is a big data analysis service based on search terms and viewing videos provided by Google LLC, and attempts to use it in various fields are continuing. In this study, we endeavored to introduce the 'value as a research tool' of the Google Trends, that has emerged along with technological advancements, through research on 'whether toothaches really occur frequently on rainy days'. Methods: Keywords were selected as objectively as possible by applying web crawling and text mining techniques, and the keyword "bi" meaning rain in Korean was added to verify the reliability of Google Trends data. The correlation was statistically analyzed using precipitation and temperature data provided by the Korea Meteorological Agency and daily search volume data provided by Google Trends. Results: Keywords "chi-gwa", "chi-tong", and "chung-chi" were selected, which in Korean mean 'dental clinic', 'toothache', and 'tooth decay' respectively. A significant correlation was found between the amount of precipitation and the search volume of tooth decay. No correlation was found between precipitation and other keywords or other combinations. It was natural that a very significant correlation was found between the amount of precipitation, temperature, and the search volume of "bi". Conclusion: Rain seems to actually be a cause of toothache, and if objective keyword selection is premised, Google Trends is considered to be very useful as a research tool in the future.

• Journal of the Korean Society for information Management
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• v.41 no.2
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• pp.47-69
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• 2024

Despite many changes occurring in the objects and methods of reading, the importance of reading as the most effective means of developing human intellectual ability is consistently emphasized. However, in Korea, reading tends to be perceived as a part of tedious and rigid education or learning activities rather than an act of giving pleasure and joy while accompanied by fun and interest. In addition, compared to the high interest and emphasis on reading, discussions on reading programs to systematically implement them are relatively insufficient, and it is difficult to find a study in Korea that grasp the overall research trend in the field of reading programs. Accordingly, in order to generally examine research trends in the field of domestic reading programs, an intellectual structure analysis method based on keyword profiling was applied. In particular, basic analysis, keyword analysis, research area analysis, and analysis by period and year were performed in stages based on the keywords of theses and academic journal articles in the domestic reading program field retrieved from the RISS database. In addition, future research tasks were presented by comprehensively reviewing the research trends of domestic reading programs identified as a result of this intellectual structure analysis.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2830-2832
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• 2005

Recently, retrieval or various video data has become an important issue as more and more multimedia content services are being provided. To effectively deal with video data, a semantic-based retrieval scheme that allows for processing diverse user queries and saving them on the database is required. In this regard, this paper proposes a semantic-based video retrieval system that allows the user to search diverse meanings of video data for electrical safetyrelated educational purposes by means of automatic annotation processing. If the user inputs a keyword to search video data for electrical safety-related educational purposes, the mobile agent of the proposed system extracts the features of the video data that are afterwards learned in a continuous manner, and detailed information on electrical safety education is saved on the database. The proposed system is designed to enhance video data retrieval efficiency for electrical safety-related educational purposes.

• Proceedings of the CALSEC Conference
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• 2005.03a
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• pp.189-194
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• 2005

Many studies have been conducted to classify documents, and to extract useful information from documents. However, most search engines have used a keyword based method. This method does not search and classify documents effectively. This paper identifies structures of XML document based on the fact that the XML document has a structural document using a set theory, which is suggested by Broder, and attempts a test for clustering XML document by applying a k-nearest neighbor algorithm. In addition, this study investigates the effectiveness of the clustering technique for large scaled data, compared to the existing bitmap method, by applying a test, which reveals a difference between the clause based documents instead of using a type of vector, in order to measure the similarity between the existing methods.

• Proceedings of the KAIS Fall Conference
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• 2006.05a
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• pp.320-323
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• 2006

Recently, retrieval of various video data has become an important issue as more and more multimedia content services are being provided. To effectively deal with video data, a semantic-based retrieval scheme that allows for processing diverse user queries and saving them on the database is required. In this regard, this paper proposes a semantic-based video retrieval system that allows the user to search diverse meanings of video data for electrical safetyrelated educational purposes by means of automatic annotation processing. If the user inputs a keyword to search video data for electrical safety-related educational purposes, the mobile agent of the proposed system extracts the features of the video data that are afterwards learned in a continuous manner, and detailed information on electrical safety education is saved on the database. The proposed system is designed to enhance video data retrieval efficiency for electrical safety-related educational purposes.

• Journal of Korea Society of Industrial Information Systems
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• v.7 no.2
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• pp.40-45
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• 2002

In this paper, we design and implement an agent-based mask dance guidance system which provides multimedia information on traditional masques through WWW. When the server receives a query from the client, it produces the multimedia data by connecting several real full-motion videos, and synthesizing adequate voice data for guiding announcement. To develop an agent-based guidance system, we designed and implemented four agents such as interface agent, user modeling agent coordinator agent and data management agent. The mask dance guidance system also provides the functions of searching using the keyword and learning.

• Journal of the Korea Society of Computer and Information
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• v.10 no.6 s.38
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• pp.137-152
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• 2005

In this Paper, we Propose an efficient web-based video learning evaluation system that is tailored to individual student's characteristics through the use of user profile-based information filtering. As a means of giving video-based questions, keyframes are extracted based on the location, size, and color information, and question-making intervals are extracted by means of differences in gray-level histograms as well as time windows. In addition, through a combination of the category-based system and the keyword-based system, questions for examination are given in order to ensure efficient evaluation. Therefore, students can enhance school achievement by making up for weak areas while continuing to identify their areas of interest.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.53-77
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• 2012

This study analyses the difference of contents and tones of arguments among three Korean major newspapers, the Kyunghyang Shinmoon, the HanKyoreh, and the Dong-A Ilbo. It is commonly accepted that newspapers in Korea explicitly deliver their own tone of arguments when they talk about some sensitive issues and topics. It could be controversial if readers of newspapers read the news without being aware of the type of tones of arguments because the contents and the tones of arguments can affect readers easily. Thus it is very desirable to have a new tool that can inform the readers of what tone of argument a newspaper has. This study presents the results of clustering and classification techniques as part of text mining analysis. We focus on six main subjects such as Culture, Politics, International, Editorial-opinion, Eco-business and National issues in newspapers, and attempt to identify differences and similarities among the newspapers. The basic unit of text mining analysis is a paragraph of news articles. This study uses a keyword-network analysis tool and visualizes relationships among keywords to make it easier to see the differences. Newspaper articles were gathered from KINDS, the Korean integrated news database system. KINDS preserves news articles of the Kyunghyang Shinmun, the HanKyoreh and the Dong-A Ilbo and these are open to the public. This study used these three Korean major newspapers from KINDS. About 3,030 articles from 2008 to 2012 were used. International, national issues and politics sections were gathered with some specific issues. The International section was collected with the keyword of 'Nuclear weapon of North Korea.' The National issues section was collected with the keyword of '4-major-river.' The Politics section was collected with the keyword of 'Tonghap-Jinbo Dang.' All of the articles from April 2012 to May 2012 of Eco-business, Culture and Editorial-opinion sections were also collected. All of the collected data were handled and edited into paragraphs. We got rid of stop-words using the Lucene Korean Module. We calculated keyword co-occurrence counts from the paired co-occurrence list of keywords in a paragraph. We made a co-occurrence matrix from the list. Once the co-occurrence matrix was built, we used the Cosine coefficient matrix as input for PFNet(Pathfinder Network). In order to analyze these three newspapers and find out the significant keywords in each paper, we analyzed the list of 10 highest frequency keywords and keyword-networks of 20 highest ranking frequency keywords to closely examine the relationships and show the detailed network map among keywords. We used NodeXL software to visualize the PFNet. After drawing all the networks, we compared the results with the classification results. Classification was firstly handled to identify how the tone of argument of a newspaper is different from others. Then, to analyze tones of arguments, all the paragraphs were divided into two types of tones, Positive tone and Negative tone. To identify and classify all of the tones of paragraphs and articles we had collected, supervised learning technique was used. The Na$\ddot{i}$ve Bayesian classifier algorithm provided in the MALLET package was used to classify all the paragraphs in articles. After classification, Precision, Recall and F-value were used to evaluate the results of classification. Based on the results of this study, three subjects such as Culture, Eco-business and Politics showed some differences in contents and tones of arguments among these three newspapers. In addition, for the National issues, tones of arguments on 4-major-rivers project were different from each other. It seems three newspapers have their own specific tone of argument in those sections. And keyword-networks showed different shapes with each other in the same period in the same section. It means that frequently appeared keywords in articles are different and their contents are comprised with different keywords. And the Positive-Negative classification showed the possibility of classifying newspapers' tones of arguments compared to others. These results indicate that the approach in this study is promising to be extended as a new tool to identify the different tones of arguments of newspapers.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.1
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• pp.43-48
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• 2006

The educational system has been changed owing to Web, which is most actively used on internet and has the characteristics of providing suitable environments for implementing constructivism study theory. WBI(Web Based Instruction), web-mediated teaching form for students at a long distance, has the advantages of possible interact between instructors and learners, offering a great variety of learning materials, and overcome the spatiotemporal restriction. This paper focuces on the construction of learning surroundings where the learner-centered, active learning can be done by design and Implementation of web based instruct system providing a sham examination with an item pool system. The web based Self-directed Learning system for word processor qualifying exams on this paper, can be mentioned as a real item pool that the question is not setting each time by the instructors but can be reused by reference on item pool bank, designed the number of question. It helps the learner Self-directed Learning study with evaluation during the web based instruct process and immediate feedback. It also provides the chance to research some similar using keyword. To sum up, this system can amplify the efficiency of study.