• 제목/요약/키워드: Key word

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Microblog User Geolocation by Extracting Local Words Based on Word Clustering and Wrapper Feature Selection

  • Tian, Hechan;Liu, Fenlin;Luo, Xiangyang;Zhang, Fan;Qiao, Yaqiong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제14권10호
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    • pp.3972-3988
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    • 2020
  • Existing methods always rely on statistical features to extract local words for microblog user geolocation. There are many non-local words in extracted words, which makes geolocation accuracy lower. Considering the statistical and semantic features of local words, this paper proposes a microblog user geolocation method by extracting local words based on word clustering and wrapper feature selection. First, ordinary words without positional indications are initially filtered based on statistical features. Second, a word clustering algorithm based on word vectors is proposed. The remaining semantically similar words are clustered together based on the distance of word vectors with semantic meanings. Next, a wrapper feature selection algorithm based on sequential backward subset search is proposed. The cluster subset with the best geolocation effect is selected. Words in selected cluster subset are extracted as local words. Finally, the Naive Bayes classifier is trained based on local words to geolocate the microblog user. The proposed method is validated based on two different types of microblog data - Twitter and Weibo. The results show that the proposed method outperforms existing two typical methods based on statistical features in terms of accuracy, precision, recall, and F1-score.

소음환경에서 표적단어의 예상도가 조절된 한국어의 문장검사목록개발 시안 (Development of a test of Korean Speech Intelligibility in Noise(KSPIN) using sentence materials with controlled word predictability)

  • 김진숙;배소영;이정학
    • 음성과학
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    • 제7권2호
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    • pp.37-50
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    • 2000
  • This paper describes a test of everyday speech understanding ability, in which a listener's utilization of the context-situational information of speech is assessed, and is compared with the utilization of acoustic-phonetic information. The test items are sentences which are presented in a babble type of noise, and the listener response is the key word in the sentence. The key words are always two-syllabic nouns and the questioning sentences are added to obtain the responding key words. Two types of sentences are used. One is the high-predictable sentences for which the key word is somewhat predictable from the context. The other is the low-predictable sentences for which the key-word cannot be predicted from the context. Both types are included in six 40-item forms of the test, which are balanced for intelligibility, key-word familiarity and predictability, phonetic content, and length. Performance of normally hearing listeners shows significantly different functions for various signal-to-noise ratios. The potential applications of this test, particularly in the assessment of speech understanding ability in the hearing impaired, are discussed.

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텍스트마이닝을 이용한 한국응급구조학회지 중심단어 분석 (Analysis of key words published with the Korea Society of Emergency Medical Services journal using text mining)

  • 권찬양;양현모
    • 한국응급구조학회지
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    • 제24권1호
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    • pp.85-92
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    • 2020
  • Purpose: The purpose of this study was to analyze the English abstract key words found within the Korea Society of Emergency Medical Services journal using text mining techniques to determine the adherence of these terms with Medical Subject Headings (MeSH) and identify key word trends. Methods: We analyzed 212 papers that were published from 2012 to 2019. R software, web scraping, and frequency analysis of key words were conducted using R's basic and text mining packages. Additionally, the Word Clouds package was used for visualization. Results: The average number of key words used per study was 3.9. Word cloud visualization revealed that CPR was most prominent in the first half and emergency medical technician was most frequently used during the second half. There were a total of 542 (64.9%) words that exactly matched the MeSH listed words. A total of 293 (35%) key words did not match MeSH listed words. Conclusion: Researchers should obey submission rules. Further, journals should update their respective submission rules. MeSH key words that are frequently cited should be suggested for use.

음절 복원 알고리즘을 이용한 핵심어 오류 보정 시스템 (Key-word Error Correction System using Syllable Restoration Algorithm)

  • 안찬식;오상엽
    • 한국컴퓨터정보학회논문지
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    • 제15권10호
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    • pp.165-172
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    • 2010
  • 어휘 인식 시스템의 오류 보정방법으로는 오류 패턴매칭 기반 방법과 어휘의미 패턴 기반방법이있으며, 이들 방법에서는 오류 보정을 위해 핵심어를 의미적으로 분석하지 못하는 문제점을 가지고 있다. 이를 개선하기 위해 본 논문에서는 음절 복원 알고리즘을 이용한 핵심어 오류 보정 시스템을 제안한다. 인식된 음소 열을 의미 분석 과정을 거쳐 음소가 갖는 의미를 파악하고 음절 복원 알고리즘을 통해 음운 변동이 적용되기 이전의 문자열로 복원하므로 핵심어를 명확히 분석하고 오인식을 줄일 수 있다. 시스템 분석을 위해 음소 유사율과 신뢰도를 이용하여 오류 보정율을 구하였으며, 어휘 인식 과정에서 오류로 판명된 어휘에 대하여 오류 보정을 수행하였다. 에러 패턴 학습을 이용한 방법과 오류 패턴 매칭 기반 방법, 어휘 의미 패턴 기반 방법의 성능 평가 결과 3.0%의 인식 향상율을 보였다.

ID 기반 키동의 프로토콜을 이용한 PayWord 시스템 (PayWord System using ID-based tripartite Key Agreement Protocol)

  • 이현주;이충세
    • 한국통신학회논문지
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    • 제29권2C호
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    • pp.348-353
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    • 2004
  • 모바일 환경에서 전자 지불 메카니즘이 구축되기 위채서는 안전성과 효율성을 갖춘 지불 시스템의 개발이 필요하다. 기존의 PayWord 프로토콜은 판매자와 거래를 할 때마다 판매자의 인증서를 생성해야 하기 때문에 연산량이 빈번해진다. 본 논문에서는 유한체 $F_{q}$에서 타원곡선(Elliptic Cue Cryptosystem)을 이용한 ID 기반 3자간의 키 동의 프로토콜에 의해 생성된 세션키로써 개체간의 인증이 이루어지기 때문에 알고리즘 연산이 감소된다. 특히, ID 기반 공개키 암호 시스템을 적용하여 속도의 향상 및 위장 공격(Man-in-the-middle attacks)과 Forward secrecy에 안전하다.

4대 해외 패션 컬렉션의 디자인 key-word 비교분석 - 2018년 패션 컬렉션을 중심으로 - (Comparative analysis on design key-word of the four major international fashion collections - focus on 2018 fashion collection -)

  • 김새봄;이은숙
    • 한국의상디자인학회지
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    • 제21권3호
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    • pp.109-119
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    • 2019
  • The purpose of this study is to examine fashion trends and the direction of the four fashion collections by analyzing the design key-words of the four major international fashion collections in 2018. The data of this study was collected by extracting the key-words from Marie Claire Korea in 2018, with the total of the collected data numbering 2,144. The data was analyzed by text mining using the R program and word-cloud, and a co-occurrence network analysis was conducted. The results of this study are as follows: First, the key-words of fashion collection designs in 2018 were fringe and ruffle detail, silk and denim fabric, vivid color, stripe and check pattern, pants suit item, and oversized silhouette, focusing on romanticism and sport. Second, seasonal characteristics of the fashion collections were pastel colors in S/S, primary and vivid colors in F/W. Details were embroidery and cutouts in S/S, patchwork and fringe in F/W. Third, the design trends of the four major fashion collections were presented in the Paris collection: stripes, check patterns, embroidery, lace, tailoring, draping, romanticism, and glamor. In the Milan collection, checks, prints, denim, and minidresses reflected sport and romanticism. The London collection included fringe, ruffles, floral patterns, flower patterns, and romanticism. The New York collections included vivid colors, neon colors, pastel colors, oversize silhouettes, bodysuits, and long dresses.

의미 분석과 형태소 분석을 이용한 핵심어 인식 시스템 (Key-word Recognition System using Signification Analysis and Morphological Analysis)

  • 안찬식;오상엽
    • 한국멀티미디어학회논문지
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    • 제13권11호
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    • pp.1586-1593
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    • 2010
  • 확률적 패턴 매칭과 동적 패턴 매칭의 어휘 인식 오류 보정 방법에서는 핵심어를 기반으로 문장을 의미론적으로 분석하므로 형태론적 변형에 따른 핵심어 분석이 어려운 문제점을 가지고 있다. 이를 해결하기 위해 본 연구에서는 음절 복원 알고리즘에서 형태소 분석을 이용하여 인식된 음소 열을 의미 분석 과정을 통해 음소의 의미를 파악하고 형태론적 분석으로 문장을 복원하여 어휘 오인식률을 감소하였다. 시스템 분석을 위해 음소 유사률과 신뢰도를 이용하여 오류 보정률을 구하였으며, 어휘 인식 과정에서 오류로 판명된 어휘에 대하여 오류 보정을 수행하였다. 에러 패턴 학습을 이용한 방법과 오류 패턴 매칭 기반 방법, 어휘 의미 패턴 기반 방법의 성능 평가 결과 2.0%의 인식 향상률을 보였다.

Topic Analysis of Foreign Policy and Economic Cooperation: A Text Mining Approach

  • Jiaen Li;Youngjun Choi
    • Journal of Korea Trade
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    • 제26권8호
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    • pp.37-57
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    • 2022
  • Purpose -International diplomacy is key for the cohesive economic growth of countries around the world. This study aims to identify the major topics discussed and make sense of word pairs used in sentences by Chinese senior leaders during their diplomatic visits. It also compares the differences between key topics addressed during diplomatic visits to developed and developing countries. Design/methodology - We employed three methods: word frequency, co-word, and semantic network analysis. Text data are crawling state and official visit news released by the Ministry of Foreign Affairs of the People's Republic of China regarding diplomatic visits undertaken from 2015-2019. Findings - The results show economic and diplomatic relations most prominently during state and official visits. The discussion topics were classified according to nine centrality keywords most central to the structure and had the maximum influence in China. Moreover, the results showed that China's diplomatic issues and strategies differ between developed and developing countries. The topics mentioned in developing countries were more diverse. Originality/value - Our study proposes an effective approach to identify key topics in Chinese diplomatic talks with other countries. Moreover, it shows that discussion topics differ for developed and developing countries. The findings of this research can help researchers conduct empirical studies on diplomacy relationships and extend our method to other countries. Additionally, it can significantly help key policymakers gain insights into negotiations and establish a good diplomatic relationship with China.

모바일 전자상거래를 위한 ID 기반 지불 프로토콜 (ID-based Payment Protocol for Mobile Electronic Commerce)

  • 이현주;김선신;이충세
    • 한국정보과학회논문지:정보통신
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    • 제31권4호
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    • pp.405-413
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    • 2004
  • M-commerce가 활성화되기 위한 주요 요건 중의 하나는 안전성과 효율성을 갖춘 전자 지불 시스템을 개발하는 것이다. 본 논문에서는 ID 기반 공개키 암호 시스템을 이용하여 다중 거래에 적용할 수 있는 효율적인 소액 지불 프로토콜 (Micro-Payment Protocol)을 제안한다. 기존의 PayWord 시스템은 다수의 판매자와 거래를 하기 위해 매번 판매자의 인증서를 생성하였다. 본 논문에서는 인증서 대신 유한체 $F_q$에서 타원곡선(Elliptic Curve Cryptosystem)을 이용한 Weil pairing에 의해 생성된 세션키를 거래에 사용하기 때문에 알려진 키 공격(Known key attacks)과 위장 공격(Man-in-the-middle attacks)에 안전하다.