• Journal of the Korean Geosynthetics Society
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• v.22 no.2
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• pp.47-54
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• 2023

In this paper, we propose the technique of optimal search keyword extraction and retrieval for news article classification. The proposed technique was verified as an example of identifying trends related to North Korean construction. A representative Korean media platform, BigKinds, was used to select sample articles and extract keywords. The extracted keywords were vectorized using word embedding and based on this, the similarity between the extracted keywords was examined through cosine similarity. In addition, words with a similarity of 0.5 or higher were clustered based on the top 10 frequencies. Each cluster was formed as 'OR' between keywords inside the cluster and 'AND' between clusters according to the search form of the BigKinds. As a result of the in-depth analysis, it was confirmed that meaningful articles appropriate for the original purpose were extracted. This paper is significant in that it is possible to classify news articles suitable for the user's specific purpose without modifying the existing classification system and search form.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.2008-2013
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• 2010

Recently, a lot of newsstands and mini station-store are operated as a store at the platform of subway. But the papers and magazines which are main articles for sale could be as the source of fire ignitable because those kind of easy flammable. Therefore the newsstands could be the target for fire. In this paper, numerical fire simulations for the News-stand were conducted to develop the news-stand fire simulation methodology for fire safety.

• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.458-464
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• 2020

Drones are being spreaded for the purposes such as construction, logistics, scientific research, recording, toy and so on. However, anti-drone related technologies which make the opposite drones neutralized are also widely being researched and developed because some drones are being used for crime or terror. The range of anti-drone related technologies can be divided into detection, identification and neutralization. The drone neutralization methods are divided into Soft-kill one which blocks the detected drones using jamming and Hard-kill one which destroys the detected ones physically. In this paper, Google and Naver domestic news articles related to anti-drone were gathered. Analyzing the domestic news articles, 8 of related technologies using RF, GNSS, Radar and so on were found. Regarding as this, the general features and usage status of those technologies were described and those on anti-drone for each company and agency were gathered and analyzed.

• The KIPS Transactions:PartB
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• v.11B no.7 s.96
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• pp.785-792
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• 2004

With recent progress of related multimedia computing technologies, it is necessay to retrieve diverse types of multimedia data based on multi-media content and their relationships. However, different from alphanumeric data, it is difficult to provide relevant multimedia information, be-cause multimedia contents and their relationships are implied in multimedia data. Therefore, in case of a multimedia news service system that is a representative multimedia application, most of new services provide relevant news about text articles and retrieval of multimedia news such as video news or image news are provided independently. In this paper, we present an XML-based multimedia news management system, which provides integrating, retrieval, and delivery of relevant multimedia news. Our data model composed of media object, relationship object, and view object represents diverse types of multimedia news content and semantically related multimedia news. In addition, a proposed view mechanism makes it possible to customize multimedia news, and therefore provides multimedia news efficiently.

• Journal of the Korea Society for Simulation
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• v.31 no.3
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• pp.35-44
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• 2022

In this study, we analyze and forecast quantum computer technology trends. Previous research has been mainly focused on application fields centered on technology for quantum computer technology trends analysis. Therefore, this paper analyzes important quantum computer technologies and performs future signal detection and prediction, for a more market driven technical analysis and prediction. As analyzing words used in news articles to identify rapidly changing market changes and public interest. This paper extends conference presentation of Cha & Chang (2022). The research is conducted by collecting domestic news articles from 2019 to 2021. First, we organize the main keywords through text mining. Next, we explore future quantum computer technologies through analysis of Term Frequency - Inverse Document Frequency(TF-IDF), Key Issue Map(KIM), and Key Emergence Map (KEM). Finally, the relationship between future technologies and supply and demand is identified through random forests, decision trees, and correlation analysis. As results of the study, the interest in artificial intelligence was the highest in frequency analysis, keyword diffusion and visibility analysis. In terms of cyber-security, the rate of mention in news articles is getting overwhelmingly higher than that of other technologies. Quantum communication, resistant cryptography, and augmented reality also showed a high rate of increase in interest. These results show that the expectation is high for applying trend technology in the market. The results of this study can be applied to identifying areas of interest in the quantum computer market and establishing a response system related to technology investment.

• The Mathematical Education
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• v.48 no.3
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• pp.265-285
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• 2009

In this study, we investigate the science and mathematics articles in Hansungsunbo and Hansungjubo which are the first modernistic newspapers in Korea. Hansungsunbo was published from October 31, 1883 to December 4, 1884 and Hansungjubo was issued from January 25, 1886 to July, 1888. While these papers were published, Korea had concluded a treaty with America(1882), England(1883), Germany(1883), Russia, and France(1884). Therefore, Korea had a lot of problems with commercial relations, the civilization and enlightenment of the Korean society. In this situation, some leaders who had the enlightenment thought published these two papers in order to inform the Korean people of the worldwide news on the politics, economy, history, science and technology, and so on. In this paper, we bring up the title and the contents on the science articles and the mathematics test problems of 'Dongmoonguan' and 'Chunjinmoobi School'.

• Journal of Korean Clinical Nursing Research
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• v.25 no.3
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• pp.209-220
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• 2019

Purpose: A significant amount of public opinion about nurse bullying is expressed on the internet. The purpose of this study was to analyze the linkage structures among words extracted from comments on internet articles related to nurse workplace bullying using semantic network analysis. Methods: From February 2018 to April 2019, comments made on news articles posted to the Daum and Naver web portal containing keywords such as "nurse", "Taeum", and "bullying" were collected using a web crawler written in Python. A morphological analysis performed with Open Korean Text in KoNLPy generated 54 major nodes. The frequencies, eigenvector centralities, and betweenness centralities of the 54 nodes were calculated and semantic networks were visualized using the UCINET and NetDraw programs. Convergence of iterated correlations (CONCOR) analysis was performed to identify structural equivalence. Results: This paper presents results about March 2018 and January 2019 because these months had highest number of articles. Of the 54 major nodes, "nurse", "hospital", "patient", and "physician" were the most frequent and had the highest eigenvector and betweenness centralities. The CONCOR analysis identified work environment, nurse, gender, and military clusters. Conclusion: This study structurally explored public opinion about nurse bullying through semantic network analysis. It is suggested that various studies on nursing phenomena will be conducted using social network analysis.

• Journal of Digital Convergence
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• v.17 no.2
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• pp.195-200
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• 2019

Nowadays as the use of mobile communication devices such as smart phones and tablets and the use of Computer is expanded, data is being collected exponentially on the Internet. In addition, due to the development of SNS, users can freely communicate with each other and share information in various fields, so various opinions are accumulated in the from of big data. Accordingly, big data analysis techniques are being used to find out the difference between the response of the general public and the response of the media. In this paper, we analyzed the public response in SNS about child allowance and childbirth grant and analyzed the response of the media. Therefore we gathered articles and comments of users which were posted on Twitter for a certain period of time and crawling the news articles and applied sentiment analysis. From these data, we compared the opinion of the public posted on SNS with the response of the media expressed in news articles. As a result, we found that there is a different response to some national policy between the public and the media.

• Journal of Information Technology Services
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• v.14 no.2
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• pp.159-176
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• 2015

As a public medium and one of the big data sources that is accumulated informally and real time, online news comments or replies are considered a significant resource to understand mentalities of article readers. The comments are also being regarded as an important medium of WOM (Word of Mouse) about products, services or the enterprises. If the diffusing effect of the comments is referred to as the degrees of agreement and disagreement from an angle of WOM, figuring out which characteristics of the comments would influence the agreements or the disagreements to the comments in very early stage would be very worthwhile to establish a comment-based eWOM (electronic WOM) strategy. However, investigating the effects of the characteristics of the comments on eWOM effect has been rarely studied. According to this angle, this study aims to conduct an empirical analysis which understands the characteristics of comments that affect the numbers of agreement and disagreement, as eWOM performance, to particular news articles which address a specific product, service or enterprise per se. While extant literature has focused on the quantitative attributes of the comments which are collected by manually, this paper used text mining techniques to acquire the qualitative attributes of the comments in an automatic and cost effective manner.

• Korean Journal of Cognitive Science
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• v.26 no.4
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• pp.435-452
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• 2015

Recent researches on Entity Linking(EL) have attempted to disambiguate entities by using a knowledge base to handle the semantic relatedness and up-to-date information. However, EL for tweets using a knowledge base is still unsatisfactory, mainly because the tweet data are mostly composed of short and noisy contexts and real-time issues. The EL system the present work builds up links ambiguous entities to the corresponding entries in a given knowledge base via exploring the news articles and the user history. Using news articles, the system can overcome the problem of Wikipedia coverage (i.e., not handling real-time issues). In addition, given that users usually post tweets related to their particular interests, the current system referring to the user history robustly and effectively works with a small size of tweet data. In this paper, we propose an approach to building an EL system that links ambiguous entities to the corresponding entries in a given knowledge base through the news articles and the user history. We created a dataset of Korean tweets including ambiguous entities randomly selected from the extracted tweets over a seven-day period and evaluated the system using this dataset. We use accuracy index(number of correct answer given by system/number of data set) The experimental results show that our system achieves a accuracy of 67.7% and outperforms the EL methods that exclusively use a knowledge base.