• Title, Summary, Keyword: 네트워크 자질

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An Analysis of Teacher Training Programs focusing on the Reflect Qualities of teachers in Gifted Education (영재교육 담당교사의 자질 반영을 중심으로 한 교사 연수 프로그램 분석)

  • Cho, Kyu-Seong;Chung, Duk-Ho;Park, Kyeong-Jin;Kim, Hee-Jin;Park, Seon-Ok
    • Journal of Gifted/Talented Education
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    • v.24 no.4
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    • pp.543-559
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    • 2014
  • The purpose of this study was to analyze the teacher training programs focusing on reflect qualities of teachers in gifted education. A total of 20 teacher training programs were collected from the office of education, the teacher training center of university and the remote training center. These teacher training programs were analyzed using a semantic network analysis. The analysis showed that 'curriculum', 'teaching and learning' and 'development of curriculum' were emphasized in teacher training programs. Therefore, teacher training programs are operated with an emphasis on teacher's professional qualities. The analysis also revealed that many of the teacher training programs were dealt with professional and teaching faculty's qualities more than affective qualities. Therefore, it is necessary to reorganize the teacher training programs to be diversified and balanced. Furthermore, in order to improve teacher's quality equally, we suggest a systematic training program should be pot in place.

Construction of Research Fronts Using Factor Graph Model in the Biomedical Literature (팩터그래프 모델을 이용한 연구전선 구축: 생의학 분야 문헌을 기반으로)

  • Kim, Hea-Jin;Song, Min
    • Journal of the Korean Society for information Management
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    • v.34 no.1
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    • pp.177-195
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    • 2017
  • This study attempts to infer research fronts using factor graph model based on heterogeneous features. The model suggested by this study infers research fronts having documents with the potential to be cited multiple times in the future. To this end, the documents are represented by bibliographic, network, and content features. Bibliographic features contain bibliographic information such as the number of authors, the number of institutions to which the authors belong, proceedings, the number of keywords the authors provide, funds, the number of references, the number of pages, and the journal impact factor. Network features include degree centrality, betweenness, and closeness among the document network. Content features include keywords from the title and abstract using keyphrase extraction techniques. The model learns these features of a publication and infers whether the document would be an RF using sum-product algorithm and junction tree algorithm on a factor graph. We experimentally demonstrate that when predicting RFs, the FG predicted more densely connected documents than those predicted by RFs constructed using a traditional bibliometric approach. Our results also indicate that FG-predicted documents exhibit stronger degrees of centrality and betweenness among RFs.

Images of Competencies of Science Teachers in Elementary and Secondary School Students (초, 중, 고등학생들의 과학 교사 자질에 대한 이미지)

  • Kim, Youngshin;Cho, Yunjung;Lim, Soo-min
    • Journal of Science Education
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    • v.44 no.1
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    • pp.61-73
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    • 2020
  • Teachers are the most important factor contributing to determining the quality of education. Therefore, the quality of teachers should be improved to enhance the quality of education. Teacher's competencies are defined as the skills required for teaching profession, that is, the ability to perform not only in teaching activities, but also in guidance and class management. The purpose of this study is to analyze the competencies of science teachers that elementary, middle and high school students want. To this end, 332 elementary, middle and high school students were asked to describe their preferred science teacher's competencies and avoiding science teacher's competencies as an open questionnaire. The resulting concepts were analyzed by semantic network analysis (SNA). The results of this study are as follows: 1) The competencies of science teachers that students prefer varied. This suggests that most students think positively about science teachers. In addition, it is possible to show students the positive or preferred competencies of teachers in various ways. 2) The students wanted teachers to explain the theories and concepts related to scientific phenomena through experiments. They also preferred hands-on activities and experience in science class. 3) The students put emphasis on the class-related contents in the competencies of science teachers. Accordingly, the image of science teachers and science itself should be enhanced through the improvement of science teaching methods and positive attitudes toward students. It is expected that further research on the image according to specific teaching methods of science teachers will be conducted based on the findings of this study.

Noun Link Relation Research Of Verb '-Kata (가다)' for Korean Syntactic Analysis (한국어 구문 해석을 위한 동사 '가다'의 명사 결합 관계 연구)

  • Park, Keon-Sook
    • Annual Conference on Human and Language Technology
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    • pp.207-216
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    • 1998
  • 본 논문에서는 한국어 구문 해석을 위해 동사 중심의 구문 틀 정보를 구축하고, 나아가 결합 빈도가 높은 명사와의 결합 관계를 하나의 네트워크로 구성하는 구문 해석의 방법을 제안한다. 동사 중심의 구문 틀과 명사의 의미 자질은 구문 해결에서 아주 중요한 역할을 하는 것으로, 구문의 비문 여부를 가리는 데 도움을 준다. 그러나 명사의 의미 자질은 경계가 모호하여 구문의 적격성(wellformedness)을 가리기에는 부족한 점이 많다. 따라서 동사와 명사의 결합 관계를 이용하면 구문의 의미적 적격성을 좀 더 명시적으로 가릴 수 있다. 한국어에서 기본 동사이고, 초등학교 교과서에서 사용된 빈도가 아주 높은 동사 '가다'를 가지고 구체적으로 구문 틀 정보와 결합 명사의 의미 자질 및 결합 관계를 정리하였다.

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Students' and Teachers' Perception on the Roles and Qualifications of Teacher Librarians based on the Semantic Network Analysis (언어네트워크 분석을 통한 사서교사 역할 및 자질에 대한 학생과 교사의 인식 연구)

  • Lee, Yeon-Ok
    • Journal of Korean Library and Information Science Society
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    • v.51 no.3
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    • pp.81-102
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    • 2020
  • The purpose of this study is to examine the students' and teachers' perception about the roles and qualifications of teacher librarians. For this purpose, data were collected through survey from students and teachers at secondary schools and the data were analyzed by semantic network analysis. The results of the research are as follows: First, students usually perceived the role of teacher librarians as 'library management', and teachers did as 'reading education'. Second, among the roles of teacher librarians, it was confirmed that students' and teachers' perceptions of 'information literacy instruction and library instruction' were very weak. Third, while the students' perception of the role of a teacher librarian as a 'teaching collaborator' such as 'teaching and learning support' and 'library assisted instruction and collaborative instruction' was weak, teachers recognized the role of teacher librarians as 'teaching collaborators'. Fourth, students and teachers perceived high levels of 'information service', which consists of 'book recommendation and guide activities'. Finally, it was investigated that 'professionalism' plays a central role in the students' and teachers' perception about the qualities of teacher librarians. These results can be used to establish the role of teacher librarians, develop response strategies for students and teachers, and improve their awareness.

Extraction of Protein-Protein Interactions based on Convolutional Neural Network (CNN) (Convolutional Neural Network (CNN) 기반의 단백질 간 상호 작용 추출)

  • Choi, Sung-Pil
    • KIISE Transactions on Computing Practices
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    • v.23 no.3
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    • pp.194-198
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    • 2017
  • In this paper, we propose a revised Deep Convolutional Neural Network (DCNN) model to extract Protein-Protein Interaction (PPIs) from the scientific literature. The proposed method has the merit of improving performance by applying various global features in addition to the simple lexical features used in conventional relation extraction approaches. In the experiments using AIMed, which is the most famous collection used for PPI extraction, the proposed model shows state-of-the art scores (78.0 F-score) revealing the best performance so far in this domain. Also, the paper shows that, without conducting feature engineering using complicated language processing, convolutional neural networks with embedding can achieve superior PPIE performance.

Experimental Study for Effective Combination of Opinion Features (효과적인 의견 자질 결합을 위한 실험적 연구)

  • Han, Kyoung-Soo
    • Journal of the Korean Society for information Management
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    • v.27 no.3
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    • pp.227-239
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    • 2010
  • Opinion retrieval is to retrieve items which are relevant to the user information need topically and include opinion about the topic. This paper aims to find a method to represent user information need for effective opinion retrieval and to analyze the combination methods for opinion features through various experiments. The experiments are carried out in the inference network framework using the Blogs06 collection and 100 TREC test topics. The results show that our suggested representation method based on hidden 'opinion' concept is effective, and the compact model with very small opinion lexicon shows the comparable performance to the previous model on the same test data set.

An Informetric Analysis on Intellectual Structures with Multiple Features of Academic Library Research Papers (복수 자질에 의한 지적 구조의 계량정보학적 분석연구: 국내 대학도서관 분야 연구논문을 대상으로)

  • Choi, Sang-Hee
    • Journal of the Korean Society for information Management
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    • v.28 no.2
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    • pp.65-78
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    • 2011
  • The purpose of this study is to identify topic areas of academic library research using two informetric methods; word clustering and Pathfinder network. For the data analysis, 139 articles published in major library and information science journals from 2005 to 2009 were collected from the Korean Science Citation Index database. The keywords that represent research topics were gathered from two sections: an and titles in references. Results showed that reference titles usefully represent topics in detail, and combinings and reference titles can produce an expanded topic map.

Enhancing the Performance of Blog Retrieval by User Tagging and Social Network Analysis (사용자 태그와 중심성 지수를 이용한 블로그 검색 성능 향상에 관한 연구)

  • Kim, Eun-Hee;Chung, Young-Mee
    • Journal of the Korean Society for information Management
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    • v.27 no.1
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    • pp.61-77
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    • 2010
  • Blogs are now one of the major information resources on the web. The purpose of this study is to enhance the performance of blog retrieval by means of user assigned tags and trackback information. To this end, retrieval experiments were performed with a dataset of 4,908 blog pages together with their associated trackback URLs. In the experiments, text terms, user tags, and network centrality values based on trackbacks were variously combined as retrieval features. The experimental results showed that employing user tags and network centrality values as retrieval features in addition to text words could improve the performance of blog retrieval.

Extracting Core Events Based on Timeline and Retweet Analysis in Twitter Corpus (트위터 문서에서 시간 및 리트윗 분석을 통한 핵심 사건 추출)

  • Tsolmon, Bayar;Lee, Kyung-Soon
    • KIPS Transactions on Software and Data Engineering
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    • v.1 no.1
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    • pp.69-74
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    • 2012
  • Many internet users attempt to focus on the issues which have posted on social network services in a very short time. When some social big issue or event occurred, it will affect the number of comments and retweet on that day in twitter. In this paper, we propose the method of extracting core events based on timeline analysis, sentiment feature and retweet information in twitter data. To validate our method, we have compared the methods using only the frequency of words, word frequency with sentiment analysis, using only chi-square method and using sentiment analysis with chi-square method. For justification of the proposed approach, we have evaluated accuracy of correct answers in top 10 results. The proposed method achieved 94.9% performance. The experimental results show that the proposed method is effective for extracting core events in twitter corpus.