• Title/Summary/Keyword: 핵심어 유사도

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A Bibliographic Study on the Calvin Theological Journal (칼빈 신학교 학술지에 대한 계량서지학적 분석에 관한 연구)

  • Yoo, Yeong Jun;Lee, Jae Yun
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.27 no.4
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    • pp.125-145
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    • 2016
  • This study aimed at finding theological trends of Calvin Theological Journal by analyzing Library of Congress Subject Headings (LCSH). The study performed the time-series analysis and the analysis of distinctive terms by examining the main authors and the subject headings of the articles published in Calvin Theological Journal during 45 years. We also proposed a new method of dividing the analysis period with the change of authors and subject headings. In the analysis results, the 18 main authors had the three clusters and shared Calvin and the Reformed Theology, the Bible. The reformed characteristics were shown in the first and second period, but the reformed theology was at the margins. The frequency of Calvin became small in the third period, the frequency of the reformed theology became bigger than before, but it was at the perimeters. Literary criticism was clustered independently. There were lots of the terms of the reformed theology in the analysis of the distinctive terms in all three periods and especially in the 2-1 period science and religion were included as the distinctive terms. Therefore, the theological tendency of the Calvin Theological Journal seemed the reformed theology and Old Testament.

Graph Learning System for Analyzing Bias among News Using Keyword Distance Model (주제어 문장거리를 이용한 뉴스 편향성 분석 그래프 학습)

  • Cho Chanwoo;Cho Chanhyung
    • Annual Conference on Human and Language Technology
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    • 2023.10a
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    • pp.533-538
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    • 2023
  • 문서에서 저자의 의도와 주제, 그 안에 포함된 감성을 분석하는 것은 자연어 연구의 핵심적인 주제이다. 이와 유사하게 특정 글에 포함된 정치적 문화적 편향을 분석하는 것 역시 매우 의미 있는 연구주제이다. 우리는 최근 발생한 한 사건에 대하여 여러 신문사와 해당 신문사에서 생산한 기사를 중심으로 해당 글의 정치적 편향을 정량화 하는 방법을 제시한다. 그 방법은 선택된 주제어들의 문장 공간에서의 거리를 중심으로 그래프를 생성하고, 생성된 그래프의 기계학습을 통하여 편향과 특징을 분석하였다. 그리고 그 그래프들의 시간적 변화를 추적하여 특정 신문사에서 특정 사건에 대한 입장이 시간적으로 어떻게 변화하였는지를 동적으로 보여주는 그래프 애니메이션 시스템을 개발하였다. 실험을 위하여 최근 이슈에 대하여 12개의 신문사에서 약 2000여 개의 기사를 수집하였다. 그 결과, 약 82%의 정확도로 일반적으로 알려진 정치적 편향을 예측할 수 있었다. 또한, 학습 데이터에 쓰이지 않은 신문기사를 활용하여도 같은 정도의 정확도를 보임을 알 수 있었다. 우리는 이를 통하여 신문기사에서의 정치적 편향은 작성자나 신문사의 특성이 아니라 주제어들의 문장 공간에서의 거리 관계로 특성화할 수 있음을 보였다. 할 수 있다.

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Searching Similar Example-Sentences Using the Needleman-Wunsch Algorithm (Needleman-Wunsch 알고리즘을 이용한 유사예문 검색)

  • Kim Dong-Joo;Kim Han-Woo
    • Journal of the Korea Society of Computer and Information
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    • v.11 no.4 s.42
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    • pp.181-188
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    • 2006
  • In this paper, we propose a search algorithm for similar example-sentences in the computer-aided translation. The search for similar examples, which is a main part in the computer-aided translation, is to retrieve the most similar examples in the aspect of structural and semantical analogy for a given query from examples. The proposed algorithm is based on the Needleman-Wunsch algorithm, which is used to measure similarity between protein or nucleotide sequences in bioinformatics. If the original Needleman-Wunsch algorithm is applied to the search for similar sentences, it is likely to fail to find them since similarity is sensitive to word's inflectional components. Therefore, we use the lemma in addition to (typographical) surface information. In addition, we use the part-of-speech to capture the structural analogy. In other word, this paper proposes the similarity metric combining the surface, lemma, and part-of-speech information of a word. Finally, we present a search algorithm with the proposed metric and present pairs contributed to similarity between a query and a found example. Our algorithm shows good performance in the area of electricity and communication.

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A Study on the International Research Trend in Education Development focused on Text Network Analysis(2002~2017) (교육개발협력에 관한 국제 학술지 연구 동향 고찰 : 텍스트 네트워크 분석을 중심으로(2002~2017))

  • Kim, Sang-Mi;Kim, Young-Hwan;Cho, Won-Gyeum
    • Korean Journal of Comparative Education
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    • v.28 no.1
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    • pp.1-24
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    • 2018
  • The objective of the article is to find the research trends and the main traits presented in the keywords on abstracts of research articles of "International Journal of Education Development" from 2002 to 2017. To do this, Text Network Analysis(TNA) was applied targeting 966 papers on the journal and the major research outcomes are as follows. First, the frequency analysis on the keywords showed that the keywords like Administration of education program, Schools and instruction, Regional public administration, Educational support service, Elementary education, and Elementary and secondary school were analyzed more than 100 times and also high in centrality degree. Second, the analysis results of the keywords presented in those research articles by development goal periods showed that several new keywords like Elementary education, Elementary and secondary school, Education quality, Secondary education, Educational planning have emerged frequently after SDGs and these keywords showed high in their centrality analysis. Third, the analysis on education level showed that the keywords like Elementary education, Administration of education program, School children were high in frequency and centrality degree in Elementary level. In secondary level, Schools and instruction, Administration of education program, Academic achievement were high, and in high level, college and university was high, respectively.

Semi-supervised GPT2 for News Article Recommendation with Curriculum Learning (준 지도 학습과 커리큘럼 학습을 이용한 유사 기사 추천 모델)

  • Seo, Jaehyung;Oh, Dongsuk;Eo, Sugyeong;Park, Sungjin;Lim, Heuiseok
    • Annual Conference on Human and Language Technology
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    • 2020.10a
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    • pp.495-500
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    • 2020
  • 뉴스 기사는 반드시 객관적이고 넓은 시각으로 정보를 전달하지 않는다. 따라서 뉴스 기사를 기존의 추천 시스템과 같이 개인의 관심사나 사적 정보를 바탕으로 선별적으로 추천하는 것은 바람직하지 않다. 본 논문에서는 최대한 객관적으로 다양한 시각에서 비슷한 사건과 인물에 대해서 판단할 수 있도록 유사도 기반의 기사 추천 모델을 제시한다. 길이가 긴 문서 사이의 유사도를 측정하기 위해 GPT2 [1]언어 모델을 활용했다. 이 과정에서 단방향 디코더 모델인 GPT2 [1]의 단점을 추가 학습으로 개선했으며, 저장 공간의 효율과 핵심 문단 추출을 위해 BM25 [2]함수를 사용했다. 그리고 준 지도 학습 [3]을 통해 유사도 레이블링이 되어있지 않은 최신 뉴스 기사에 대해서도 자가 학습을 진행했으며, 이와 함께 길이가 긴 문단에 대해서도 효과적으로 학습할 수 있도록 문장 길이를 기준으로 3개의 단계로 나누어진 커리큘럼 학습 [4]방식을 적용했다.

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한국어 합성 동사성 명사의 어휘구조와 다중 동사성명사 구문

  • 류병래
    • Proceedings of the Korean Society for Language and Information Conference
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    • 2001.06a
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    • pp.141-144
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    • 2001
  • 본 논문의 목적은 ‘다중 동사성 명사 구문’(Multiple Verbal Noun Construe-tions)의 논항실현 양상을 이론 중립적으로 고찰해 보고, 이 분석을 제약기반 문법 이론인 최근의 핵 심어주도 구구조문법 (Head-driven Phrase Structure Grammar)틀 안에서, 특히 다중계승위 계를 가정하는 제약기반 어휘부를 기반으로 형식화해 논항의 실현과정을 기술하고 설명하는 것이다. 우선 일본어의 유사한 현상을 분석한 Grimshaw & Mester (1988)의 격실현 양상에 관한 일반화를 기반으로 한국어 동사성명사구문의 논항실현 양상을 ‘논항전이’ (argument transfer)라는 이론적 장치를 이용해 형식화할 수 있음을 보이고, 동사성 합성명사의 논항구조를 만들기 위해 ‘논항합성’(argument composition)이라는 이론적 장치를 제안한다. 나아가서 다중 동사성 명사구문의 논항실현 과정에서 보이는 겹격표지 현상을 ‘격 복사’(case copying)를 제안해 동사성 명사의 격표지가 합성 명사에서 분리되어 문장단위에서 실현될 때 동일한 격을 복사해 실현한다는 점을 주장하고자 한다. 이 주장을 뒷받침하기 위해 수동과 능동 등 문법기능의 변화현상에서 하위범주화된 요소들의 격변화가 자의적이 아님을 실례를 들어 보여 주고자 한다. 일본어의 경동사 (light verbs)에 관한 분석 인 Grimshaw Meste, (1988) 이래 한국어에서도 이와 유사한 구문에 대한 재조명이 활발하게 이루어져 왔다 (Ryu (1993b), 채희락 (1996), Chae (1997) 등 참조). 한국어에서 ‘하다’와 동사성명사(verbal nouns)가 결합하여 이루어진 ‘동사성명사구문’ (Verbal Noun Constructions)에 대한 기존의 논의는 대부분 하나의 동사성 명사가 ‘하다’나 ‘되다등 소위 문법기능을 바꾸는 ‘경동사’들과 결합하여 복합술어가 되는 문법적 현상에 초점이 맞춰져 있었다. 그와 비교해서 동사성 명사의 어근이 두 개 이상 결합하여 동사성명사들끼리 합성명사(compound nouns)를 이루고 그 동사성 합성명사가 문법기능의 변화를 바꾸는 ‘경동사’와 결합하여 이루어진 복합술어에 대해서는 논의가 거의 없는 형편이다. 특히 이 지적은 핵심어주도 구절구조문법틀 내에서는 논란의 여지가 없다. 본 논문의 대상은 바로 이러한 합성 동사성명사의 논항구조와 동사성명사에 의해 하위범주화된 논항들의 문법적 실현양상이다.

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Automatic Text Categorization based on Semi-Supervised Learning (준지도 학습 기반의 자동 문서 범주화)

  • Ko, Young-Joong;Seo, Jung-Yun
    • Journal of KIISE:Software and Applications
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    • v.35 no.5
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    • pp.325-334
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    • 2008
  • The goal of text categorization is to classify documents into a certain number of pre-defined categories. The previous studies in this area have used a large number of labeled training documents for supervised learning. One problem is that it is difficult to create the labeled training documents. While it is easy to collect the unlabeled documents, it is not so easy to manually categorize them for creating training documents. In this paper, we propose a new text categorization method based on semi-supervised learning. The proposed method uses only unlabeled documents and keywords of each category, and it automatically constructs training data from them. Then a text classifier learns with them and classifies text documents. The proposed method shows a similar degree of performance, compared with the traditional supervised teaming methods. Therefore, this method can be used in the areas where low-cost text categorization is needed. It can also be used for creating labeled training documents.

A Study on Out-of-Vocabulary Rejection Algorithms using Variable Confidence Thresholds (가변 신뢰도 문턱치를 사용한 미등록어 거절 알고리즘에 대한 연구)

  • Bhang, Ki-Duck;Kang, Chul-Ho
    • Journal of Korea Multimedia Society
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    • v.11 no.11
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    • pp.1471-1479
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    • 2008
  • In this paper, we propose a technique to improve Out-Of-Vocabulary(OOV) rejection algorithms in variable vocabulary recognition system which is much used in ASR(Automatic Speech Recognition). The rejection system can be classified into two categories by their implementation method, keyword spotting method and utterance verification method. The utterance verification method uses the likelihood ratio of each phoneme Viterbi score relative to anti-phoneme score for deciding OOV. In this paper, we add speaker verification system before utterance verification and calculate an speaker verification probability. The obtained speaker verification probability is applied for determining the proposed variable-confidence threshold. Using the proposed method, we achieve the significant performance improvement; CA(Correctly Accepted for keyword) 94.23%, CR(Correctly Rejected for out-of-vocabulary) 95.11% in office environment, and CA 91.14%, CR 92.74% in noisy environment.

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Korea National College of Agriculture and Fisheries in Naver News by Web Crolling : Based on Keyword Analysis and Semantic Network Analysis (웹 크롤링에 의한 네이버 뉴스에서의 한국농수산대학 - 키워드 분석과 의미연결망분석 -)

  • Joo, J.S.;Lee, S.Y.;Kim, S.H.;Park, N.B.
    • Journal of Practical Agriculture & Fisheries Research
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    • v.23 no.2
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    • pp.71-86
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    • 2021
  • This study was conducted to find information on the university's image from words related to 'Korea National College of Agriculture and Fisheries (KNCAF)' in Naver News. For this purpose, word frequency analysis, TF-IDF evaluation and semantic network analysis were performed using web crawling technology. In word frequency analysis, 'agriculture', 'education', 'support', 'farmer', 'youth', 'university', 'business', 'rural', 'CEO' were important words. In the TF-IDF evaluation, the key words were 'farmer', 'dron', 'agricultural and livestock food department', 'Jeonbuk', 'young farmer', 'agriculture', 'Chonju', 'university', 'device', 'spreading'. In the semantic network analysis, the Bigrams showed high correlations in the order of 'youth' - 'farmer', 'digital' - 'agriculture', 'farming' - 'settlement', 'agriculture' - 'rural', 'digital' - 'turnover'. As a result of evaluating the importance of keywords as five central index, 'agriculture' ranked first. And the keywords in the second place of the centrality index were 'farmers' (Cc, Cb), 'education' (Cd, Cp) and 'future' (Ce). The sperman's rank correlation coefficient by centrality index showed the most similar rank between Degree centrality and Pagerank centrality. The KNCAF articles of Naver News were used as important words such as 'agriculture', 'education', 'support', 'farmer', 'youth' in terms of word frequency. However, in the evaluation including document frequency, the words such as 'farmer', 'dron', 'Ministry of Agriculture, Food and Rural Affairs', 'Jeonbuk', and 'young farmers' were found to be key words. The centrality analysis considering the network connectivity between words was suitable for evaluation by Cd and Cp. And the words with strong centrality were 'agriculture', 'education', 'future', 'farmer', 'digital', 'support', 'utilization'.

A Bibliometric Study on Foreign Reformed Theological Journals (외국 개혁신학 학술지에 대한 계량서지학적 연구)

  • Yoo, Yeong Jun;Lee, Jae Yun
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.30 no.3
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    • pp.149-170
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    • 2019
  • This study aimed at analyzing the 6 foreign reformed theological journals and index terms, authors to find out the intellectual structures and the characteristics of the journals, the authors. First, analyzing the index terms, we analyzed the main keywords and the increasing trend by period, second, analyzing the journals, we analyzed the main subject of them and the subjects of distinguishing features by the journals, third we analyzed the authors' profiling. The index terms were clustered four big clusters and 23 small clusters. The journals were clustered the two clusters, and we also analyzed the index terms to distinguish a journal from other journals. The authors were clustered the six clusters, the index terms the clusters of the authors shared were similar to the results of the two analyses. The biblical teachings of The Old Testament and the New Testament and reformed theology were core subject terms and it was consistent in the results of these three analyses. This study mainly aimed at analyzing the 6 foreign reformed theological journals, and we found out that the parts of the results of this study were similar to the results of analyzing the domestic reformed theological journals. Therefore, there should be more researches needed to figure out what the results of this study mean to Korean reformed theology.