• Title/Summary/Keyword: 빈도 기반 텍스트 분석

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A study on frame transition of personal information leakage, 1984-2014: social network analysis approach (사회연결망 분석을 활용한 개인정보 유출 프레임 변화에 관한 연구: 1984년-2014년을 중심으로)

  • Jeong, Seo Hwa;Cho, Hyun Suk
    • Journal of Digital Convergence
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    • v.12 no.5
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    • pp.57-68
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    • 2014
  • This article analyses frame transition of personal information leakage in Korea from 1984 to 2014. In order to investigate the transition, we have collected newspaper article's titles. This study adopts classification, text network analysis(by co-occurrence symmetric matrix), and clustering techniques as part of social network analysis. Moreover, we apply definition of centrality in network in order to reveal the main frame formed in each of four periods. As a result, accessibility of personal information is extended from public sector to private sector. The boundary of personal information leakage is expanded to overseas. Therefore it is urgent to institutionalize the protection of personal information from a global perspective.

Sentence Similarity Analysis using Ontology Based on Cosine Similarity (코사인 유사도를 기반의 온톨로지를 이용한 문장유사도 분석)

  • Hwang, Chi-gon;Yoon, Chang-Pyo;Yun, Dai Yeol
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.05a
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    • pp.441-443
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    • 2021
  • Sentence or text similarity is a measure of the degree of similarity between two sentences. Techniques for measuring text similarity include Jacquard similarity, cosine similarity, Euclidean similarity, and Manhattan similarity. Currently, the cosine similarity technique is most often used, but since this is an analysis according to the occurrence or frequency of a word in a sentence, the analysis on the semantic relationship is insufficient. Therefore, we try to improve the efficiency of analysis on the similarity of sentences by giving relations between words using ontology and including semantic similarity when extracting words that are commonly included in two sentences.

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Out of Vocabulary Word Extractor based on a Syllable n-gram (음절 n-gram 기반의 미등록 어휘 추정기 구현)

  • Shin, Junsoo;Hong, Chohee
    • Annual Conference on Human and Language Technology
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    • 2013.10a
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    • pp.139-141
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    • 2013
  • 다양한 콘텐츠가 생성됨에 따라 신조어 및 미등록어도 다양한 형태로 나타나고 있다. 이러한 신조어 및 미등록어는 텍스트 처리 단계에서 오분석 되어 성능 저하의 원인이 된다. 본 논문은 이러한 문제를 해결하기 위해서 대량의 문서로부터 신조어 및 미등록 어휘를 추정하는 방법에 대해서 제안한다. 제안 방법은 대량의 문서로부터 음절 n-gram을 추출한 뒤, 각 n-gram에서 n을 한음절 축소 및 확장 시켜, (n+1)gram, (n-1)gram을 추가적으로 추출한다. 추출된 음절 n-gram을 기준으로 (n+1)gram, (n-1)gram과의 빈도 차이를 계산하여 빈도차가 급격하게 발생하는 구간을 신조어 및 미등록 어휘로 추정한다. 실험결과 신조어 뿐만 아니라 트위터, 미투데이 등과 같은 도메인에 종속적인 미등록 어휘도 추출되는 것을 확인할 수 있었다.

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A Study on Text Mining Methods to Analyze Civil Complaints: Structured Association Analysis (민원 분석을 위한 텍스트 마이닝 기법 연구: 계층적 연관성 분석)

  • Kim, HyunJong;Lee, TaiHun;Ryu, SeungEui;Kim, NaRang
    • Journal of Korea Society of Industrial Information Systems
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    • v.23 no.3
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    • pp.13-24
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    • 2018
  • For government and public institutions, civil complaints containing direct requirements of citizens can be utilized as important data in developing policies. However, it is difficult to draw accurate requirements using text mining methods since the nature of the complaint text is unstructured. In this study, a new method is proposed that draws the exact requirements of citizens, improving the previous text mining in analyzing the data of civil complaints. The new text-mining method is based on the principle of Co-Occurrences Structure Map, and it is structured by two-step association analysis, so that it consists of the first-order related word and a second-order related word based on the core subject word. For the analysis, 3,004 cases posted on the electronic bulletin board of Busan City for the year 2016 are used. This study's academic contribution suggests a method deriving the requirements of citizens from the civil affairs data. As a practical contribution, it also enables policy development using civil service data.

Social Media Bigdata Analysis Based on Information Security Keyword Using Text Mining (텍스트마이닝을 활용한 정보보호 키워드 기반 소셜미디어 빅데이터 분석)

  • Chung, JinMyeong;Park, YoungHo
    • Journal of Korea Society of Industrial Information Systems
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    • v.27 no.5
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    • pp.37-48
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    • 2022
  • With development of Digital Technology, social issues are communicated through digital-based platform such as SNS and form public opinion. This study attempted to analyze big data from Twitter, a world-renowned social network service, and find out the public opinion. After collecting Twitter data based on 14 keywords for 1 year in 2021, analyzed the term-frequency and relationship among keyword documents with pearson correlation coefficient using Data-mining Technology. Furthermore, the 6 main topics that on the center of information security field in 2021 were derived through topic modeling using the LDA(Latent Dirichlet Allocation) technique. These results are expected to be used as basic data especially finding key agenda when establishing strategies for the next step related industries or establishing government policies.

A novel on Context Information Analysis and Prediction Process using Text Mining (텍스트 마이닝을 이용한 상황 정보 분석 및 예측 프로세스에 관한 연구)

  • Jung, Se-hoon;Kang, Joo-hee;Kim, Jong-chan;Sim, Chun-bo
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2015.10a
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    • pp.1039-1040
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    • 2015
  • 최근 IoT 및 인공지능 기술을 활용한 상황 정보 예측 서비스가 각광을 받고 있다. 본 논문에서는 특정 메타 데이터(Meta Data)로부터 입력되는 정보를 기반으로 상황 정보 분석 및 예측하는 프로세스를 제안한다. 주성분 분석 및 데이터의 집단화(Corpus), 문서 매트릭스(Document Matrix), 단어 빈도수(Frequency)에 따른 데이터 전처리 과정을 통해 상황정보 데이터를 확보한다. 또한 연관 규칙분석을 통해 분류된 데이터의 연관성을 분석하여 예측 데이터의 연관성을 확보한다. 제안하는 상황정보 분석 및 예측 모델은 R을 적용하여 설계한다.

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The Study on Data Governance Research Trends Based on Text Mining: Based on the publication of Korean academic journals from 2009 to 2021 (텍스트 마이닝을 활용한 데이터 거버넌스 연구 동향 분석: 2009년~2021년 국내 학술지 논문을 중심으로)

  • Jeong, Sun-Kyeong
    • Journal of Digital Convergence
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    • v.20 no.4
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    • pp.133-145
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    • 2022
  • As a result of the study, the poorest keywords were information, big data, management, policy, government, law, and smart. In addition, as a result of network analysis, related research was being conducted on topics such as data industry policy, data governance performance, defense, governance, and data public. The four topics derived through topic modeling were "DG policy," "DG platform," "DG in laws," and "DG implementation," of which research related to "DG platform" showed an increasing trend, and "DG implementation" tended to shrink. This study comprehensively summarized data governance-related studies. Data governance needs to expand research areas from various perspectives and related fields such as data management and data integration policies at the organizational level, and related technologies. In the future, we can expand the analysis targets for overseas data governance and expect follow-up studies on research directions and policy directions in industries that require data-based future industries such as Industry 4.0, artificial intelligence, and Metaverse.

A Trend Analysis and Policy proposal for the Work Permit System through Text Mining: Focusing on Text Mining and Social Network analysis (텍스트마이닝을 통한 고용허가제 트렌드 분석과 정책 제안 : 텍스트마이닝과 소셜네트워크 분석을 중심으로)

  • Ha, Jae-Been;Lee, Do-Eun
    • Journal of Convergence for Information Technology
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    • v.11 no.9
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    • pp.17-27
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    • 2021
  • The aim of this research was to identify the issue of the work permit system and consciousness of the people on the system, and to suggest some ideas on the government policies on it. To achieve the aim of research, this research used text mining based on social data. This research collected 1,453,272 texts from 6,217 units of online documents which contained 'work permit system' from January to December, 2020 using Textom, and did text-mining and social network analysis. This research extracted 100 key words frequently mentioned from the analyses of data top-level key word frequency, and degree centrality analysis, and constituted job problem, importance of policy process, competitiveness in the respect of industries, and improvement of living conditions of foreign workers as major key words. In addition, through semantic network analysis, this research figured out major awareness like 'employment policy', and various kinds of ambient awareness like 'international cooperation', 'workers' human rights', 'law', 'recruitment of foreigners', 'corporate competitiveness', 'immigrant culture' and 'foreign workforce management'. Finally, this research suggested some ideas worth considering in establishing government policies on the work permit system and doing related researches.

Analysis of Job Data on Media (미디어에 나타난 직업 관련 데이터의 분석)

  • Ban, ChaeHoon;Jung, YoonSeung;Jeong, DongMin
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2018.05a
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    • pp.152-155
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    • 2018
  • 과거와는 비교 할 수 없을 만큼 방대한 양의 데이터가 생산되는 정보화 시대에서 과거와 현재의 데이터를 비교 분석하는 것이 매우 중요하다. 이러한 데이터를 분석하는 도구인 R은 통계 기반의 정보 분석을 가능하게 하는 언어와 환경이다. 본 논문에서는 R을 이용하여 미디어에 나타난 직업 관련 빅데이터를 분석한다. 다양한 미디어에서 직업 관련 데이터를 수집하고 어떠한 텍스트가 분포되어 있는지 빈도 조사를 수행한다.

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Analyzing the Study Trends of 'Sense of Place' Using Text Mining Techniques (텍스트마이닝 기법을 활용한 국내외 장소성 관련 연구동향 분석)

  • Lee, Ina;Kim, Hea-Jin
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.30 no.2
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    • pp.189-209
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    • 2019
  • Main Path Analysis (MPA) is one of the text mining techniques that extracts the core literature that contributes knowledge transfer based on citation information in the literature. This study applied various text mining techniques to abstract of the paper related with sense-of-place, which is published at Korea and abroad from 1990 to 2018 so that could discuss in a macro perspective. The main path analysis results showed that from 1990, overseas research on sense-of-place has been carried out in the order of personal identity, public land management, environmental education and urban development-related areas. Also, by using the network analysis, this study found that sense-of-place was discussed at various levels in Korea, including urban development, culture, literature, and history. On the other hand, it has been found that there are few topic changes in international studies, and that discussions on health, identity, landscape and urban development have been going on steadily since the 1990s. This study has implications that it presents a new perspective of grasping the overall flow of relevant research.