• Title/Summary/Keyword: 텍스트 시각화

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Improving Visual Object Query language (VOQL) by Introducing Visual Elements and visual Variables (시각 요소와 시각 변수를 통한 시각 객체 질의어(VOQL)의 개선)

  • Lee, Seok-Gyun
    • The Transactions of the Korea Information Processing Society
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    • v.6 no.6
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    • pp.1447-1457
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    • 1999
  • Visual Object Query language(VOQL) proposed recently is a visual object-oriented database query language which can effectively represent queries on complex structured data, since schema information is visually included in query expressions. VOQL, which is a graph-based query language with inductively defined semantics, can concisely represent various text-based path expressions by graph, and clearly convey the semantics of complex path expressions. however, the existing VOQL assumes that all the attributes are multi-valued, and cannot visualize the concept of binding of object variables. therefore, VPAL query expressions are not intuitive, so that it is difficult to extend the existing VOQL theoretically. In this paper, we propose VOQL that improved on these problems. The improved VOQL visualizes the result of a single-valued attribute and that of a multi-valued attribute as a visual element and a subblob, respectively, and specifies the binding of object variables by introducing visual variables, so that the improved VOQL intuitively and clearly represents the semantics of queries.

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KONG-DB: Korean Novel Geo-name DB & Search and Visualization System Using Dictionary from the Web (KONG-DB: 웹 상의 어휘 사전을 활용한 한국 소설 지명 DB, 검색 및 시각화 시스템)

  • Park, Sung Hee
    • Journal of the Korean Society for information Management
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    • v.33 no.3
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    • pp.321-343
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    • 2016
  • This study aimed to design a semi-automatic web-based pilot system 1) to build a Korean novel geo-name, 2) to update the database using automatic geo-name extraction for a scalable database, and 3) to retrieve/visualize the usage of an old geo-name on the map. In particular, the problem of extracting novel geo-names, which are currently obsolete, is difficult to solve because obtaining a corpus used for training dataset is burden. To build a corpus for training data, an admin tool, HTML crawler and parser in Python, crawled geo-names and usages from a vocabulary dictionary for Korean New Novel enough to train a named entity tagger for extracting even novel geo-names not shown up in a training corpus. By means of a training corpus and an automatic extraction tool, the geo-name database was made scalable. In addition, the system can visualize the geo-name on the map. The work of study also designed, implemented the prototype and empirically verified the validity of the pilot system. Lastly, items to be improved have also been addressed.

A Study on the Issue Lifecycle through the Analysis of News Texts - A Case of Samsung Galaxy Note 7 - (신문기사 분석을 통한 이슈 라이프사이클에 관한 연구 - 삼성 갤럭시노트7 사례 -)

  • Heo, Pil Hee;Kim, Yang Sok;Lee, Choong Kwon
    • Smart Media Journal
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    • v.7 no.4
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    • pp.99-105
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    • 2018
  • It is often the case that products or services on the market are causing problems, which hurt the business and image of the company. Responding appropriately to the problem and minimizing the damage is very important to business organizations. This study collected and analyzed the news articles related to the recall of the Galaxy Note 7, which was developed and launched by Samsung Electronics, one of the smartphone market leaders. Based on the issue lifecycle, the characteristics of the news were expressed by stages and the contents of the news were analyzed and visualized using association rules. The results of this study are expected to help business organizations to understand the changes and trends of issues and search for counter measures.

Text Mining and Visualization of Unstructured Data Using Big Data Analytical Tool R (빅데이터 분석 도구 R을 이용한 비정형 데이터 텍스트 마이닝과 시각화)

  • Nam, Soo-Tai;Shin, Seong-Yoon;Jin, Chan-Yong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.9
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    • pp.1199-1205
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    • 2021
  • In the era of big data, not only structured data well organized in databases, but also the Internet, social network services, it is very important to effectively analyze unstructured big data such as web documents, e-mails, and social data generated in real time in mobile environment. Big data analysis is the process of creating new value by discovering meaningful new correlations, patterns, and trends in big data stored in data storage. We intend to summarize and visualize the analysis results through frequency analysis of unstructured article data using R language, a big data analysis tool. The data used in this study was analyzed for total 104 papers in the Mon-May 2021 among the journals of the Korea Institute of Information and Communication Engineering. In the final analysis results, the most frequently mentioned keyword was "Data", which ranked first 1,538 times. Therefore, based on the results of the analysis, the limitations of the study and theoretical implications are suggested.

Visualizing Unstructured Data using a Big Data Analytical Tool R Language (빅데이터 분석 도구 R 언어를 이용한 비정형 데이터 시각화)

  • Nam, Soo-Tai;Chen, Jinhui;Shin, Seong-Yoon;Jin, Chan-Yong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.05a
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    • pp.151-154
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    • 2021
  • Big data analysis is the process of discovering meaningful new correlations, patterns, and trends in large volumes of data stored in data stores and creating new value. Thus, most big data analysis technology methods include data mining, machine learning, natural language processing, and pattern recognition used in existing statistical computer science. Also, using the R language, a big data tool, we can express analysis results through various visualization functions using pre-processing text data. The data used in this study was analyzed for 21 papers in the March 2021 among the journals of the Korea Institute of Information and Communication Engineering. In the final analysis results, the most frequently mentioned keyword was "Data", which ranked first 305 times. Therefore, based on the results of the analysis, the limitations of the study and theoretical implications are suggested.

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Visualizing Article Material using a Big Data Analytical Tool R Language (빅데이터 분석 도구 R 언어를 이용한 논문 데이터 시각화)

  • Nam, Soo-Tai;Shin, Seong-Yoon;Jin, Chan-Yong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.05a
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    • pp.326-327
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    • 2021
  • Newly, big data utilization has been widely interested in a wide variety of industrial fields. Big data analysis is the process of discovering meaningful new correlations, patterns, and trends in large volumes of data stored in data stores and creating new value. Thus, most big data analysis technology methods include data mining, machine learning, natural language processing, and pattern recognition used in existing statistical computer science. Also, using the R language, a big data tool, we can express analysis results through various visualization functions using pre-processing text data. The data used in this study were analyzed for 29 papers in a specific journal. In the final analysis results, the most frequently mentioned keyword was "Research", which ranked first 743 times. Therefore, based on the results of the analysis, the limitations of the study and theoretical implications are suggested.

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Implementation of AESA Radar Integration Analysis System by using Heterogeneous Media

  • Min-Jung Kang
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.3
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    • pp.117-125
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    • 2024
  • In this paper, implement and propose an Active Electronically Scanned Array (AESA) radar integration analysis system which specialized for radar development by using heterogeneous media. Most analysis systems are used to analyze and improve the cause of defects, so they help the test easier. However, previous log analysis systems that operate only based on text are not intuitive and difficult to find the information user want at once if there is a lot of log information. so when an equipment defect occurs, there are limitations in analyzing the cause of defect. Therefore, the analysis system in this paper utilizes heterogeneous media. The media defined in this paper refers to recording text-based data, displaying data as image or video and visualizing data. The proposed analysis system classifies and stores data that transmitted and received between radar devices, radar target detection and Tracking algorithm data, etc. also displays and visualizes radar operation results and equipment defect information in real time. With this analysis system, it can quickly provide information what user want and assistance in developing high quality radar.

Design and Implementation of Visual Environment for Parallel Object-Oriented Programming (병렬 객체지향 프로그래밍을 위한 시각 환경의 설계 및 구현)

  • Choe, Suk-Yeong
    • The Transactions of the Korea Information Processing Society
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    • v.6 no.2
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    • pp.485-496
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    • 1999
  • Comparing with sequential programming, parallel programming has additional complexity due to the consideration of parallelism, communication and synchronization of processes. A synergism between users and compliers should be established, each assisting the other to produce high quality parallel programs. On the above underlying philosophy, we developed a parallel Object-Oriented specification language, POOSL, as preliminary works. However, it is still likely to hard for users to write parallel program because users have to consider grammar of POOSL and to write text-based parallel program. It would be more desirable to provide users wit visual environment for effective parallel programming. Therefore, we propose a visual programming environment. VEPO(Visual environment for Parallel Object-Oriented Programming), based on POOSL in order that users can develop parallel programs more easily and conveniently. It aims at supporting a programming environment in which users can represent their programs more naturally and visually I parallel manner with object-oriented concept and essential steps during parallel program development such as program specification, compilation, execution and animation of execution are integrated. VEPO has useful features for parallel processing. Especially, complicated parallel codes for synchronization and communication of processes are automatically generated in the translation phase, so users can be relieved of writing error-prone parallel codes. The system is targeted to the transputer-based parallel system, MC-3. The graphic user interface of VEPO was implemented using Visual C++. Visual programs descirbed on VEPO are translated into Inmos C and executed on MC-3.

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A Study on Visual Literacy for Picture Books: Implications for Librarians Providing Reader's Advisory Services (그림책의 시각적 문식성에 관한 연구 - 사서의 독서지원서비스를 위한 -)

  • Min, Kyeong-Rok
    • Journal of the Korean Society for Library and Information Science
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    • v.51 no.2
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    • pp.23-48
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    • 2017
  • Picture books, as a genre, are characterized by conveyance of ideas through linguistic texts, visual texts, and the complementary interactions between them. The writer of a picture book develops and delivers his or her ideas with textual contents written in a unique style, while the artist conveys the writer's ideas through pictures where things, objects, and figures are imbued with various emotions. Understanding a picture in a picture book requires an understanding of both the structure shown on the surface and the underlying structure that adapts and visualizes the philosophy and ideas of the writer. In light of the discussion above, this study proposes a method to help librarians improve their understanding of visual literacy for picture books, as visual literacy is required for the provision of readers' advisory services regarding picture books. This method, which is based on behavioral psychologist Rudolf Arnheim's theory of visual thinking, is expected to help librarians write picture book reviews or other secondary materials.

A study on unstructured text mining algorithm through R programming based on data dictionary (Data Dictionary 기반의 R Programming을 통한 비정형 Text Mining Algorithm 연구)

  • Lee, Jong Hwa;Lee, Hyun-Kyu
    • Journal of Korea Society of Industrial Information Systems
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    • v.20 no.2
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    • pp.113-124
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    • 2015
  • Unlike structured data which are gathered and saved in a predefined structure, unstructured text data which are mostly written in natural language have larger applications recently due to the emergence of web 2.0. Text mining is one of the most important big data analysis techniques that extracts meaningful information in the text because it has not only increased in the amount of text data but also human being's emotion is expressed directly. In this study, we used R program, an open source software for statistical analysis, and studied algorithm implementation to conduct analyses (such as Frequency Analysis, Cluster Analysis, Word Cloud, Social Network Analysis). Especially, to focus on our research scope, we used keyword extract method based on a Data Dictionary. By applying in real cases, we could find that R is very useful as a statistical analysis software working on variety of OS and with other languages interface.