• Review of Korea Contents Association
• /
• v.15 no.1
• /
• pp.38-43
• /
• 2017

• Journal of Digital Convergence
• /
• v.13 no.1
• /
• pp.487-493
• /
• 2015

This paper derives the strategic implications of smart learning as a sophisticated alternative to e-learning through the convergence approach of e-learning and Bigdata based on the practices of developed countries. To this, this paper derives e-Learning status and challenges issues in Korea, and then, analyzes the convergence case of e-learning and data science in major foreign advanced companies and universities. In addition, this study conducts an awareness survey on Bigdata applied for employees of e-learning companies, and then derives a strategic alternative to the Bigdata convergence-based smart learning effectiveness in the industry with the analysis of the survey data.

• International Journal of Internet, Broadcasting and Communication
• /
• v.11 no.2
• /
• pp.59-66
• /
• 2019

The emergence of new IT technologies and convergence industries, such as artificial intelligence, bigdata and the Internet of Things, is another chance for South Korea, which has established itself as one of the world's top IT powerhouses. On the other hand, however, privacy concerns that may arise in the process of using such technologies raise the task of harmonizing the development of new industries and the protection of personal information at the same time. In response, the government clearly presented the criteria for deidentifiable measures of personal information and the scope of use of deidentifiable information needed to ensure that bigdata can be safely utilized within the framework of the current Personal Information Protection Act. It strives to promote corporate investment and industrial development by removing them and to ensure that the protection of the people's personal information and human rights is not neglected. This study discusses the strategy of deidentifying personal information protection based on the analysis of fake news. Using the strategies derived from this study, it is assumed that deidentification information that is appropriate for deidentification measures is not personal information and can therefore be used for analysis of big data. By doing so, deidentification information can be safely utilized and managed through administrative and technical safeguards to prevent re-identification, considering the possibility of re-identification due to technology development and data growth.

• Annual Conference on Human and Language Technology
• /
• 2019.10a
• /
• pp.97-102
• /
• 2019

KorQuAD 2.0은 총 100,000+ 쌍으로 구성된 한국어 질의응답 데이터셋이다. 기존 질의응답 표준 데이터인 KorQuAD 1.0과의 차이점은 크게 세가지가 있는데 첫 번째는 주어지는 지문이 한두 문단이 아닌 위키백과 한 페이지 전체라는 점이다. 두 번째로 지문에 표와 리스트도 포함되어 있기 때문에 HTML tag로 구조화된 문서에 대한 이해가 필요하다. 마지막으로 답변이 단어 혹은 구의 단위뿐 아니라 문단, 표, 리스트 전체를 포괄하는 긴 영역이 될 수 있다. Baseline 모델로 구글이 오픈소스로 공개한 BERT Multilingual을 활용하여 실험한 결과 F1 스코어 46.0%의 성능을 확인하였다. 이는 사람의 F1 점수 85.7%에 비해 매우 낮은 점수로, 본 데이터가 도전적인 과제임을 알 수 있다. 본 데이터의 공개를 통해 평문에 국한되어 있던 질의응답의 대상을 다양한 길이와 형식을 가진 real world task로 확장하고자 한다.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
• /
• 2018.06a
• /
• pp.132-132
• /
• 2018

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2022.01a
• /
• pp.411-412
• /
• 2022

본 논문에서는 코로나19 뉴스와 코로나19 가짜뉴스의 데이터셋을 활용하여 입력 받은 뉴스가 가짜뉴스일 확률을 예측한다. 가짜 뉴스 본문에는 코로나19, 대통령, 정부, 가짜, 언론 등의 키워드의 빈도가 높았다. 위의 키워드를 토대로 나이브 베이즈 모델링을 하여 이를 적용해 가짜 뉴스를 가려내는 웹페이지를 개발하였다.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2016.01a
• /
• pp.111-113
• /
• 2016

빠른 속도로 쏟아지고 있는 각종 발행물, 논문들에 대한 표절 검토는 표절 검출 알고리즘을 통해 직접적인 복제, 짜깁기, 말 바꾸어 쓰기 등을 검토하거나 표절 검토자가 직접 해당 문서의 키워드를 검색하여 확인하는 방식으로 이루어지고 있다. 하지만 점점 더 늘어나는 방대한 양의 문서들에 대한 표절 검토 작업은 더욱 정교한 검토 방법론을 필요로 하고 있으며, 이를 돕기 위해 문서의 직접적인 단어나 복제 비교에서 더 나아가 문서의 내용을 비교하여 비슷한 내용의 문서들을 필터링 및 검출할 수 있는 방법을 제안한다. 문서의 내용을 비교하기 위해 키워드 추출 알고리즘을 선행하며, 이를 통해 문서의 핵심 내용을 비교할 수 있는 기반을 마련하여 표절 검토자의 작업의 정확성과 속도를 향상시키고자 한다.

• International Journal of Advanced Culture Technology
• /
• v.9 no.3
• /
• pp.345-351
• /
• 2021

This study is designed to determine how to identify misleading news articles based on natural language processing on Artificial Intelligence & Bigdata. A misleading news discrimination system and method on natural language processing is initiated according to an embodiment of this study. The natural language processing-based misleading news identification system, which monitors the misleading vocabulary database, Internet news articles, collects misleading news articles, extracts them from the titles of the collected misleading news articles, and stores them in the misleading vocabulary database. Therefore, the use of the misleading news article identification system and methods in this study does not take much time to judge because only relatively short news titles are morphed analyzed, and the use of a misleading vocabulary database provides an effect on identifying misleading articles that attract readers with exaggerated or suggestive phrases. For the aim of our study, we propose news article identification methods in natural language processing on Artificial Intelligence & Bigdata.

• International Journal of Internet, Broadcasting and Communication
• /
• v.11 no.2
• /
• pp.50-58
• /
• 2019

The clear and specific objective of this study is to design a false news discriminator algorithm for news articles transmitted on a text-based basis and an architecture that builds it into a system (H/W configuration with Hadoop-based in-memory technology, Deep Learning S/W design for bigdata and SNS linkage). Based on learning data on actual news, the government will submit advanced "fake news" test data as a result and complete theoretical research based on it. The need for research proposed by this study is social cost paid by rumors (including malicious comments) and rumors (written false news) due to the flood of fake news, false reports, rumors and stabbings, among other social challenges. In addition, fake news can distort normal communication channels, undermine human mutual trust, and reduce social capital at the same time. The final purpose of the study is to upgrade the study to a topic that is difficult to distinguish between false and exaggerated, fake and hypocrisy, sincere and false, fraud and error, truth and false.

• Mycobiology
• /
• v.50 no.5
• /
• pp.374-381
• /
• 2022

In the mating of filamentous basidiomycetes, dikaryotic mycelia are generated through the reciprocal movement of nuclei to a monokaryotic cytoplasm where a nucleus of compatible mating type resides, resulting in the establishment of two different dikaryotic strains having the same nuclei but different mitochondria. To better understand the role of mitochondria in mushrooms, we created four sets of dikaryotic strains of Lentinula edodes, including B2×E13 (B2 side) and B2×E13 (E13 side), B5×E13 (B5 side) and B5×E13 (E13 side), E8×H3 (E8 side) and E8×H3 (H3 side), and K3×H3 (K3 side) and K3×H3 (H3 side). The karyotypes and mitochondrial types of the dikaryotic strains were successfully identified by the A mating type markers and the mitochondrial variable length tandem repeat markers, respectively. Comparative analyses of the dikaryotic strains on the mycelial growth, substrate browning, fruiting characteristics, and mitochondrial gene expression revealed that certain mitochondria are more effective in the mycelial growth and the production of fruiting body, possibly through the activated energy metabolism. Our findings indicate that mitochondria affect the physiology of dikaryotic strains having the same nuclear information and therefore a selection strategy aimed at mitochondrial function is needed in the development of new mushroom strain.