• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.271-274
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• 2018

본 논문에서는 뉴스기사 데이터를 활용하여 대규모 뉴스기사를 소주제로 분류하는 군집 분석 방법을 제안한다. 또한, 분류된 뉴스기사를 사용자가 빠르게 이해하고 접할 수 있도록 핵심 문장을 추출하여 제공하는 방법을 제안한다. 분석 데이터는 포털 사이트 점유율 1위인 네이버의 경제 분야 뉴스기사를 크롤링하여 수집한다. 뉴스기사의 분석을 위해 전 처리를 통해 특수문자, 조사, 어미, 구두점 등의 불 용어 처리를 수행한다. 또한, k-means 알고리즘을 이용하여 대용량의 뉴스기사를 주제 별로 분류하는 것을 진행하며 그것을 토대로 핵심 문장을 추출한다. 추출된 핵심 문장은 분류된 뉴스기사의 주제를 나타내며 사용자에게 빠르게 정보를 전달하기 위해 활용한다. 본 논문의 연구 내용이 여러 언론사 사이트에 반영되면 사이트 품질과 사용자 만족도 향상에 기여할 수 있을 것으로 보인다.

• The Korea Swine Journal
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• v.12 no.1 s.125
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• pp.48-49
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• 1990

• The KIPS Transactions:PartB
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• v.16B no.2
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• pp.181-194
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• 2009

With the increased interest on the document copyright, many of researches related to the document plagiarism have been done up to now. The plagiarism problem of newspaper articles has attracted much interest because the plagiarism cases of the articles having much commercial values in market are currently happened very often. Many researches related to the document plagiarism have been so hard to be applied to the newspaper articles because they have strong real-time characteristics. So to detect the plagiarism of the articles, many human detectors have to read every single thousands of articles published by hundreds of newspaper companies manually. In this paper, we firstly sorted out the articles with high possibility of being copied by utilizing OpenAPI modules supported by web search companies such as Naver and Daum. Then, we measured the document similarity between selected articles and the original article and made the system decide whether the article was plagiarized or not. In experiment, we used YonHap News articles as the original articles and we also made the system select the suspicious articles from all searched articles by Naver and Daum news search services.

• Journal of KIISE
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• v.43 no.11
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• pp.1210-1215
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• 2016

Readership of online newspapers has grown with the proliferation of smart devices. However, fierce competition between Internet newspaper companies has resulted in a large increase in the number of hoax articles. Hoax articles are those where the title does not convey the content of the main story, and this gives readers the wrong information about the contents. We note that the hoax articles have certain characteristics, such as unnecessary celebrity quotations, mismatch in the title and content, or incomplete sentences. Based on these, we extract and validate features to identify hoax articles. We build a large-scale training dataset by analyzing text keywords in replies to articles and thus extracted five effective features. We evaluate the performance of the support vector machine classifier on the extracted features, and a 92% accuracy is observed in our validation set. In addition, we also present a selective bigram model to measure the consistency between the title and content, which can be effectively used to analyze short texts in general.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.6
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• pp.63-71
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• 2011

The current Web portal sites provide significant keywords with high popularity or importance; specifically, user-friendly services such as tag clouds and associated word search are provided. However, in general, since news articles are classified only with their date and categories, it is not easy for users to find other articles related to some articles while reading news articles classified with categories. And the conventional associated keyword service has not satisfied users sufficiently because it depends only upon user queries. This paper proposes a way of searching news articles by utilizing the keywords tightly associated with users' queries. Basically, the proposed method discovers a set of keyword association patterns by using the association rule mining technique that extracts association patterns for keywords by focusing upon sentences containing some keywords. The method enables users to navigate the space of associated keywords hidden in large news articles.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.3
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• pp.1345-1354
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• 2014

This paper has analyzed how the format of the text page and the contents of space surrounding the text in the news stories of the portal sites are made-up. The result of analysis showed that the formats of the text page in Naver news story were more intricate than those of Daum, Nate and Yahoo. Also, Naver was higher in the number of advertising, the type of advertising, the entertainment contents, and various types of contents than other three portals. Especially, the percentage of new story related to entertainers was the highest. It was the portal site Daum that advertised the news story most of all in its text page. In contrast, it was portal site Yahoo that inserted the advertisements least of all. But from the whole sides, it was found that the formats and contents of the text page of the news story in these three portal sites have similarly been made-up. Consequently speaking, for the serviceability of use in news story, it can be evaluated that the news service method in portal sites is higher than that in press dot coms.

• Journal of Digital Convergence
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• v.10 no.4
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• pp.129-136
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• 2012

This study is presented on the corporate advertising strategy utilizing internet on corporate social responsibility in the context of the articles. To this end, Internet articles divided into positive and negative contexts, and has even attracted the attention of Internet articles and high /low and then separated into groups on ad attitudes and corporate image, the interaction effect was examined. Firstly, the Internet, a low level of condition of the article noted, in the context of a positive than a negative context, recall rates were higher. Second, the context of Internet articles and attention on the interaction effect between attitude toward advertising appeared. Third, the context of Internet articles and attention on the interaction effects between the corporate image appeared. Finally, the context of Internet articles and attention on competitive interactions between the corporate management was effective. Thus, the context of Internet articles based on the level of attention and context to determine the effect of advertising by consumer advertising awareness and favorable attitude toward corporate advertising and corporate image enhancement and competitiveness of business management can be an effective strategic plan suggests that.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.8
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• pp.1015-1021
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• 2020

Mobile news users want news articles without advertising, meanwhile the news providers require advertisement displays in several types to attain advertising revenue. In this paper, we classified the types of advertisements on mobile news articles into fixed article type which is fixed on some areas of articles, fixed screen type which is fixed on mobile screens, and a combination type of them. In addition, we proposed a smart solution based on overlapping method which effectively organize advertisements to not distract the readers. The proposed method is similar to fixed article type and overlapping technique of advertisements on news article's photo or virtual area. The performance evaluation result shows that the proposed method provides more spaces for news articles effectively than the existing methods. Although only some areas of advertisements may be blocked according to the number or size of advertisements, the effect is not critical.

• Journal of the Korea Society of Computer and Information
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• v.29 no.6
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• pp.13-22
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• 2024

There is a need for and positive aspects of article-based advertising, but as exaggerated and disguised information is delivered due to some indiscriminate 'article-based advertisements', readers have difficulty distinguishing between general articles and article-based advertisements, leading to a lot of misinterpretation and confusion of information. is doing Since readers will continue to acquire new information and apply this information at the right time and place to bring a lot of value, it is judged to be even more important to distinguish between accurate general articles and article-like advertisements. Therefore, as differentiated information between general articles and article-like advertisements is needed, as part of this, for readers who have difficulty identifying accurate information due to such indiscriminate article-like advertisements in Internet newspapers, this paper introduces IT and AI technologies. We attempted to present a method that can be solved in terms of a system that incorporates, and this method was designed to extract articleable advertisements using a knowledge-based natural language processing method that finds and refines advertising keywords and deep learning technology.

• Proceedings of the Korean Society of Computer Information Conference
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• 2009.01a
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• pp.445-449
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• 2009

인터넷의 발달과 인터넷 문화의 보편화로 인하여 사용자들은 폭발적으로 증가하는 다양한 정보를 접할 수 있게 되었으며, 자체 생산하거나 다른 신문사들로부터 생산된 기사들을 단순 유통, 링크를 통하여 정보검색 사이트들뿐만 아니라 각종 포털 사이트, 인터넷신문사들은 많은 다양한 경로로 기사를 제공할 수 있게 되었다. 이에 따라 인터넷산문을 규정하고 법적, 테두리에 넣기 위한 법률이 제정되었으며, 인터넷신문사에 대해 기사의 자체 생산량이라는 요건 검증에 대한 요구가 증가하고 있다. 본 논문은 인터넷신문 자체기사 생산량을 측정하기 위해 필요한 기술들을 조사하고 타당성을 검토하여 이에 적합한 기술을 제시한다. 제시한 방법은 대량의 기사의 비교를 빠른 시간에 수행한 수 있도록 하기 위해 인간의 단어 인지와 관련한 경험적 정보의 반영을 통하여 변형한 편집거리 기반 방법이다. 제시하는 방법의 정확성을 검증하기 위해 실제 소량의 인터넷 신문 기사를 대상으로 실험하였다.