• 제목/요약/키워드: Language Network

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연결망 분석도구를 이용한 크리스토퍼 알렉산더 패턴언어 활용 가능성에 관한 연구 (A Study on the Possibility to Use Christopher Alexander's Pattern Language by Using Network Analysis Tool)

  • 정성욱;김문덕
    • 한국실내디자인학회논문집
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    • 제25권3호
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    • pp.31-39
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    • 2016
  • This study is aimed to increase the possibility of using the Christopher Alexander's pattern language. The methodology of this study is (i) to analyze the pattern language by using the network analysis tool in order to understand the complicate network structure of the pattern language, and (ii) to apply the Alexander's method of using the pattern language by using the network analysis tool (Gephi) and to examine the feasibility of the network analysis tool as a tool for using the pattern language. Firstly, as a result of analysing the pattern language, (i) the pattern language classified by pattern number is distinguished by the patterns of towns, buildings and construction, among which the pattern of buildings plays a key function in the networks; (ii) the buildings functions a medium connecting between the towns and the construction; and (iii) the pattern language is divided into 6 sub-modules, through which the user can select a pattern. Secondly, the result of using the network analysis tool as a tool for using the pattern language (i) suggests the new method of using the pattern language by using the network analysis tool (Gephi); (ii) makes it possible to easily figure out the characteristics of the links between the patterns; and (iii) increases the completeness of the pattern language by making it easy to find out the sub-patterns in selecting a pattern.

Deep Bi-affine Network와 스택 포인터 네트워크를 이용한 한국어 의존 구문 분석 시스템 (Korean Dependency Parsing Using Deep Bi-affine Network and Stack Pointer Network)

  • 안휘진;박찬민;서민영;이재하;손정연;김주애;서정연
    • 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
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    • 한국정보과학회언어공학연구회 2018년도 제30회 한글 및 한국어 정보처리 학술대회
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    • pp.689-691
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    • 2018
  • 의존 구문 분석은 자연어 이해 영역의 대표적인 과제 중 하나이다. 본 논문에서는 한국어 의존 구분 분석의 성능 향상을 위해 Deep Bi-affine Network 와 스택 포인터 네트워크의 앙상블 모델을 제안한다. Bi-affine 모델은 그래프 기반 방식, 스택 포인터 네트워크의 경우 그래프 기반과 전이 기반의 장점을 모두 사용하는 모델로 서로 다른 모델의 앙상블을 통해 성능 향상을 기대할 수 있다. 두 모델 모두 한국어 어절의 특성을 고려한 자질을 사용하였으며 세종 의존 구문 분석 데이터에 대해 UAS 90.60 / LAS 88.26(Deep Bi-affine Network), UAS 92.17 / LAS 90.08(스택 포인터 네트워크) 성능을 얻었다. 두 모델에 대한 앙상블 기법 적용시 추가적인 성능 향상을 얻을 수 있었다.

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언어 네트워크 분석 방법을 활용한 학술논문의 내용분석 (A Content Analysis of Journal Articles Using the Language Network Analysis Methods)

  • 이수상
    • 정보관리학회지
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    • 제31권4호
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    • pp.49-68
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    • 2014
  • 본 연구의 목적은 국내 학술논문 데이터베이스에서 검색한 언어 네트워크 분석 관련 53편의 국내 학술논문들을 대상으로 하는 내용분석을 통해, 언어 네트워크 분석 방법의 기초적인 체계를 파악하기 위한 것이다. 내용분석의 범주는 분석대상의 언어 텍스트 유형, 키워드 선정 방법, 동시출현관계의 파악 방법, 네트워크의 구성 방법, 네트워크 분석도구와 분석지표의 유형이다. 분석결과로 나타난 주요 특성은 다음과 같다. 첫째, 학술논문과 인터뷰 자료를 분석대상의 언어 텍스트로 많이 사용하고 있다. 둘째, 키워드는 주로 텍스트의 본문에서 추출한 단어의 출현빈도를 사용하여 선정하고 있다. 셋째, 키워드 간 관계의 파악은 거의 동시출현빈도를 사용하고 있다. 넷째, 언어 네트워크는 단수의 네트워크보다 복수의 네트워크를 구성하고 있다. 다섯째, 네트워크 분석을 위해 NetMiner, UCINET/NetDraw, NodeXL, Pajek 등을 사용하고 있다. 여섯째, 밀도, 중심성, 하위 네트워크 등 다양한 분석지표들을 사용하고 있다. 이러한 특성들은 언어 네트워크 분석 방법의 기초적인 체계를 구성하는 데 활용할 수 있을 것이다.

Application of Artificial Neural Network For Sign Language Translation

  • Cho, Jeong-Ran;Kim, Hyung-Hoon
    • 한국컴퓨터정보학회논문지
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    • 제24권2호
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    • pp.185-192
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    • 2019
  • In the case of a hearing impaired person using sign language, there are many difficulties in communicating with a normal person who does not understand sign language. The sign language translation system is a system that enables communication between the hearing impaired person using sign language and the normal person who does not understand sign language in this situation. Previous studies on sign language translation systems for communication between normal people and hearing impaired people using sign language are classified into two types using video image system and shape input device. However, the existing sign language translation system does not solve such difficulties due to some problems. Existing sign language translation systems have some problems that they do not recognize various sign language expressions of sign language users and require special devices. Therefore, in this paper, a sign language translation system using an artificial neural network is devised to overcome the problems of the existing system.

S&T Policy Trend Using Language Network Analysis: Focusing on Science and Technology Basic Plan

  • Kim, Yun Jong;Jeong, Dae-hyun;Oh, Hyunchul
    • Asian Journal of Innovation and Policy
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    • 제6권2호
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    • pp.111-137
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    • 2017
  • This study analyzes a language network of Science and Technology Basic Plan, which is the basis for science and technology policy in Korea, for the next Science and Technology Basic Plan. Language network analysis was adopted for a quantitative approach measuring the trend of policies. Several techniques such as keyword analysis, language network map analysis, quantitative characteristics analysis and keyword-related major-word analysis have been performed. Results show that there are common policies emphasized by all Science and Technology Basic Plans in the past, and there are also specific policies emphasized in each period of the Science and Technology Basic Plan. These specific policies come from a 'change of times' when the Science and Technology Basic Plans were established, as well as the philosophy of the national government.

Sign Language Image Recognition System Using Artificial Neural Network

  • Kim, Hyung-Hoon;Cho, Jeong-Ran
    • 한국컴퓨터정보학회논문지
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    • 제24권2호
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    • pp.193-200
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    • 2019
  • Hearing impaired people are living in a voice culture area, but due to the difficulty of communicating with normal people using sign language, many people experience discomfort in daily life and social life and various disadvantages unlike their desires. Therefore, in this paper, we study a sign language translation system for communication between a normal person and a hearing impaired person using sign language and implement a prototype system for this. Previous studies on sign language translation systems for communication between normal people and hearing impaired people using sign language are classified into two types using video image system and shape input device. However, existing sign language translation systems have some problems that they do not recognize various sign language expressions of sign language users and require special devices. In this paper, we use machine learning method of artificial neural network to recognize various sign language expressions of sign language users. By using generalized smart phone and various video equipment for sign language image recognition, we intend to improve the usability of sign language translation system.

A Study on Word Sense Disambiguation Using Bidirectional Recurrent Neural Network for Korean Language

  • Min, Jihong;Jeon, Joon-Woo;Song, Kwang-Ho;Kim, Yoo-Sung
    • 한국컴퓨터정보학회논문지
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    • 제22권4호
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    • pp.41-49
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    • 2017
  • Word sense disambiguation(WSD) that determines the exact meaning of homonym which can be used in different meanings even in one form is very important to understand the semantical meaning of text document. Many recent researches on WSD have widely used NNLM(Neural Network Language Model) in which neural network is used to represent a document into vectors and to analyze its semantics. Among the previous WSD researches using NNLM, RNN(Recurrent Neural Network) model has better performance than other models because RNN model can reflect the occurrence order of words in addition to the word appearance information in a document. However, since RNN model uses only the forward order of word occurrences in a document, it is not able to reflect natural language's characteristics that later words can affect the meanings of the preceding words. In this paper, we propose a WSD scheme using Bidirectional RNN that can reflect not only the forward order but also the backward order of word occurrences in a document. From the experiments, the accuracy of the proposed model is higher than that of previous method using RNN. Hence, it is confirmed that bidirectional order information of word occurrences is useful for WSD in Korean language.

자바를 이용한 웹 기반 원격 공압 서보 제어 시스템에 관한 연구 (A Study of Web-based Remote Pneumatic Servo Control System Using Java Language)

  • 박철오;안경관;송인성
    • 제어로봇시스템학회논문지
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    • 제9권3호
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    • pp.196-203
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    • 2003
  • Recent increase in accessibility to the internet makes it easy to use the internet-connected devices. The internet could allow any user can reach and command any device that is connected to the network. But these teleoperation systems using the internet connected device have several problems such as the network time delay, data loss and development cost of an application for the communication with each other. One feasible solution is to use local and external network line for the network time delay, transmission control protocol for data loss and Java language to reduce the development period and cost. In this study, web-based remote control system using Java language is newly proposed and implemented to a pneumatic servo control system to solve the time delay, data loss and development cost. We have conducted several experiments using pneumatic rodless cylinder through the internet and verified that the proposed remote control system was very effective.

대어휘 연속음성인식을 위한 서브네트워크 기반의 1-패스 세미다이나믹 네트워크 디코딩 (1-Pass Semi-Dynamic Network Decoding Using a Subnetwork-Based Representation for Large Vocabulary Continuous Speech Recognition)

  • 정민화;안동훈
    • 대한음성학회지:말소리
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    • 제50호
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    • pp.51-69
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    • 2004
  • In this paper, we present a one-pass semi-dynamic network decoding framework that inherits both advantages of fast decoding speed from static network decoders and memory efficiency from dynamic network decoders. Our method is based on the novel language model network representation that is essentially of finite state machine (FSM). The static network derived from the language model network [1][2] is partitioned into smaller subnetworks which are static by nature or self-structured. The whole network is dynamically managed so that those subnetworks required for decoding are cached in memory. The network is near-minimized by applying the tail-sharing algorithm. Our decoder is evaluated on the 25k-word Korean broadcast news transcription task. In case of the search network itself, the network is reduced by 73.4% from the tail-sharing algorithm. Compared with the equivalent static network decoder, the semi-dynamic network decoder has increased at most 6% in decoding time while it can be flexibly adapted to the various memory configurations, giving the minimal usage of 37.6% of the complete network size.

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언어네트워크 분석방법을 활용한 공공정보 내용분석 - 광역도시 대표 트위터 내용을 중심으로 - (A Content Analysis of Public Information using Language Network Analysis: Focused on Contents of Twitters of Metropolitans)

  • 김지현
    • 한국비블리아학회지
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    • 제27권3호
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    • pp.151-171
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    • 2016
  • 본 연구는 언어네트워크 분석방법을 통해 광역도시 대표 트위터의 정보 내용을 연도별 도시별로 심층 분석하고 정보제공 매체로서 트위터 활용에 대해 조사하였다. 언어네트워크 분석을 위한 분석도구는 KrKwic, Ucinet6, Netdraw 프로그램을 이용하였다. 연구 결과, 2014년도에는 시정 관련 정보(시민, 운영, 개최, 참여)와 시민생활 관련 정보(문화, 공원, 출근길)를 중심으로 하는 네트워크가 형성되었다. 반면 2015년에는 시정홍보에 관련 정보(시민, 문의, 개최, 시정, 행사)가 네트워크의 핵심적 역할을 차지하고 있었다. 도시별 네트워크 분석에서 연도별 도시별로 각기 다른 키워드들이 도출되었다.