• Journal of the Korean earth science society
• /
• v.34 no.2
• /
• pp.148-161
• /
• 2013

The purpose of the study was to investigate the relationship between the communication status in group and the semantic network of science gifted students. Seven small groups, 5 members in each, participated in small group activities, in which they discussed the calculation of earth density. Both the communication status in group and the semantic network of science gifted students were analyzed using KrKwic, Ucinet 6.0 for Windows. As a result, the semantic network of prime movers in group represented more frequently used words, lesser rate of component, and higher density than that of out lookers. It means that the prime movers have coherent knowledge compared to out lookers, and they output more knowledge for problem solving than out lookers. Therefore, the results of this study may be applied to evaluating the cognitive level of science gifted students and group organization for small group activity.

• Annual Conference on Human and Language Technology
• /
• 2017.10a
• /
• pp.92-96
• /
• 2017

딥 러닝 모델은 여러 히든 레이어로 구성되며, 히든 레이어의 깊이가 깊어질수록 레이어의 벡터는 높은 수준으로 추상화된다. 본 논문에서는 Encoder RNN의 레이어를 여러 층 쌓은 멀티 레이어 포인터 네트워크를 제안하고, 멀티 태스크 학습 기반인 멀티 레이어 포인터 네트워크를 이용한 한국어 의존 구문 분석 모델을 제안한다. 멀티 태스크 학습 모델은 어절 간의 의존 관계와 의존 레이블 정보를 동시에 구하여 의존 구문 분석을 수행한다. 실험 결과, 본 논문에서 제안한 모델이 기존 한국어 의존 구문 분석 연구들 보다 좋은 UAS 92.16%, LAS 89.88%의 성능을 보였다.

• Korean Association of Arts Management
• /
• no.58
• /
• pp.153-177
• /
• 2021

This study attempted to analyze language networks based on the theory of art policy in the New Normal era triggered by COVID-19 and domestic and foreign policy trends. For analysis, data containing key words of "Corona" and "Art" were collected from Google News and Web documents from March to September 2020 to extract 227 refined subject words, and the extracted subject words were analyzed as indicators of frequency and centrality of subject words through the Netminor program. In addition, visualization analysis of semantic networks has been attempted for the analysis of relationships between each topic languages. As a result of the semantic network analysis, the most frequent topic was "Corona," and "Culture and Art," "Art," "Performance," "Online" and "Support" were included in the group with the most frequencies. In the centrality analysis, "Corona" was the most popular, followed by "the era," "after," "post," "art," and "cultural arts," with high frequency, "Corona," "art," and "cultural arts" also dominated most centrality. In particular, the top-level key words in the analysis of frequency and centrality of the topic are 'online' and 'support' and 'policy'. This can be seen as indicating that the rapid rise of non-face-to-face and online content and support policies for the artistic communities are needed due to the dailyization of social distance due to COVID-19.

• The Journal of Society for e-Business Studies
• /
• v.13 no.4
• /
• pp.93-110
• /
• 2008

Reference modeling for Collaborative Networked Organizations(CNOs) has just started, and Enterprise Architecture Modeling Languages(EAMLs) for CNOs are very few. Lack of reference models makes it difficult for people to communicate with each other and lack of EAMLs also makes it difficult to implement information systems for CNOs. We propose an EAML for CNO called CAML. It supports (1) multi-level modeling based on Model- Driven Architecture of OMG's for expressive power and efficiency of implementations, and (2) multi-focus modeling based on Zachman Framework for completeness of modeling The effectiveness of the CAML is investigated through modeling of a supply chain and execution of change impact analysis.

• Journal of Gifted/Talented Education
• /
• v.25 no.5
• /
• pp.673-696
• /
• 2015

Students' perception of science-related career strongly influences the formation of career motivation in science. Especially, the high level of science gifted students' positive perceptions plays an important role in allowing them to continue to study science. This study compared perceptions of science-related career between general and gifted middle school students using semantic network analysis. To ensure this end, we first structuralize semantic networks of science-related careers that students perceived. Then, we identified the characters of networks that two different student groups showed based on the structure matrix indices of semantic network analysis. The findings illustrated that the number of science-related careers shown in science gifted students' answer is more than in general students' answer. In addition, the science gifted students perceived more diverse science-related careers than general students. Second, scientific career such as natural scientists and professors were shown in the core of science gifted students' perception network whereas non-research oriented careers such as science teachers and doctors were shown in the core of general students' perception network. In this study, we identified the science gifted students' perceptions of science-related career was significantly different from the general students'. The findings of current study can be used for the science teachers to advise science gifted students on science-related careers.

• Proceedings of the Korean Society of Disaster Information Conference
• /
• 2022.10a
• /
• pp.145-147
• /
• 2022

본 논문은 대규모 텍스트 데이터에서 이슈를 발굴할 때 사용되는 기존의 정보 네트워크 또는 지식 그래프 구축 방법의 한계점을 지적하고, 문장 단위로 정보 네트워크를 구축하는 새로운 방법에 대해서 제안한다. 먼저 문장을 구성하는 단어와 캐릭터수의 분포를 측정하며 의성어와 같은 노이즈를 제거하기 위한 역치값을 설정하였다. 다음으로 BERT 기반 언어모델을 이용하여 모든 문장을 벡터화하고, 코사인 유사도를 이용하여 두 문장벡터에 대한 유사성을 측정하였다. 오분류된 유사도 결과를 최소화하기 위하여 명사형 단어의 의미적 연관성을 비교하는 알고리즘을 개발하였다. 제안된 유사문장 비교 알고리즘의 결과를 검토해 보면, 두 문장은 서술되는 형태가 다르지만 동일한 주제와 내용을 다루고 있는 것을 확인할 수 있었다. 본 논문에서 제안하는 방법은 단어 단위 지식 그래프 해석의 어려움을 극복할 수 있는 새로운 방법이다. 향후 이슈 및 트랜드 분석과 같은 미래연구 분야에 적용하면, 데이터 기반으로 특정 주제에 대한 사회적 관심을 수렴하고, 수요를 반영한 정책적 제언을 도출하는데 기여할 수 있을 것이다

• Annual Conference on Human and Language Technology
• /
• 2018.10a
• /
• pp.13-18
• /
• 2018

구문 분석은 문장의 구조를 이해하며 의미의 중의성을 해결하는 것이다. 일반적으로 한국어는 어순 배열의 자유도가 높고 문장 성분의 생략이 빈번한 특성이 있기 때문에 의존 구문 분석이 주된 연구 대상이 되어 왔다. 스택-포인터 네트워크 모델은 의존 구문 파서에 맞게 포인터 네트워크 모델을 확장한 것이다. 스택-포인터 네트워크는 각 단어에서 의존소를 찾는 하향식 방식의 모델로 기존 모델의 장점을 유지하면서 각 단계에서 파생된 트리 정보도 사용한다. 본 연구에서는 스택-포인터 네트워크 모델을 한국어에 적용해보고 이와 함께 어절 정보를 반영하는 방법을 제안한다. 모델의 실험 결과는 세종 구문 구조를 중심어 후위(head-final)를 엄격히 준수하여 의존 구문 구조로 변환한 것을 기준으로 UAS 92.65%의 정확도를 얻었다.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.7
• /
• pp.115-124
• /
• 2022

The purpose of this study is to analyze and present keywords, trends, and language networks of keywords for each year of the pedagogical exam of the secondary teacher's employment exam for the 2019~2022 school year. The main research methods were text mining technique and language network analysis method, and analysis programs were KrKwic, Wordcloud Maker, Ucinet6, NetDraw, etc. The research results are as follows; First, keywords such as teacher, student, curriculum, class, and evaluation appeared in the top rankings, and keywords (online, wiki, discussion ceremony, information, etc.) that reflect the recent online class progress in the current COVID-19 situation also tended to appear. The keywords with high frequency of occurrence in the four-year integrated text were student(44), teacher(39), class(27), school(18), curriculum(16), online(10), and discussion method(8). Second, the overall language network of the keywords with high frequency of 4 years showed a significant level of density(0.566), total number of links(492), and average degree of links(16.4). The degree centrality was found in the order of teacher(199.0), class(197.0), student(185.0), and school(150.0). Betweenness centrality was found in the order of teacher(30.859), class(18.956), student(16.054), and school (15.745). It is expected that the results of this study will serve as data to be considered for preparatory teachers, institutions and related persons, and teachers and administrators of secondary school teacher training institutions.

• Journal of the Korean earth science society
• /
• v.40 no.3
• /
• pp.283-299
• /
• 2019

The purpose of this study is to identify the conflict frames in the process of designating the national geopark, among local residents, geology experts, and local public officials. For this purpose, the progress of the public hearing on the implementation of the national geopark in Buan and Gochang were recorded with prior consent from the participants and transferred in text form. Subsequently, we developed a reference frames for analyzing conflict frames through literature review, and analyzed the conflict frames by three researchers based on this. These analyzed conflict frames were again analyzed by using semantic network analysis. The results are as follows. In the Buan area, 'Sagree' frame, 'Snot' frame, and 'Sdisagree' frame showed high eigenvector centrality, and 'Gharm' frame and 'Cmeconomy' frame were closely connected to the 'Snot' frame located at the center of the semantic network. In the Gochang area, 'Aresource' frame, 'Cmexample' frame, and 'Gharm' frame showed high eigenvector centrality, and 'Gharm' frame and 'Cmproblemsolution' frame were closely connected to the 'Snot' frame located at the center of the semantic network. Through these results, we could see that there is still the conflict about the certification of national geopark between stakeholders in Buan, and that Gochang's stakeholders are proudly aware of their own resources. The Buan's stakeholders focused on economic gains in resolving conflicts, while Gochang's stakeholders focused on problem solving. This result of this study provides information in conflict from the national geopark in other regions.

• Journal of Korea Game Society
• /
• v.20 no.3
• /
• pp.3-14
• /
• 2020

The purpose of this paper is to analyze the factors effecting users' satisfaction on game AI for early AI diffusion. For this purpose, we interviewed 20 users who had experiences playing Blade&Soul, made by NCsoft. Interview data had been analyzed through the Semantic Network Analysis program to identify key subject words and their relations. As a result, the paper has found keywords such as patterns, contents, variety, system, and getting new users as factors effecting users satisfaction on game AI.