• Title, Summary, Keyword: visual analytics

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Introduction to Visual Analytics Research (비주얼 애널리틱스 연구 소개)

  • Oh, Yousang;Lee, Chunggi;Oh, Juyoung;Yang, Jihyeon;Kwag, Heena;Moon, Seongwoo;Park, Sohwan;Ko, Sungahn
    • Journal of The Korea Computer Graphics Society
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    • v.22 no.5
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    • pp.27-36
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    • 2016
  • As big data become more complex than ever, there has been a need for various techniques and approaches to better analyze and explore such big data. A research discipline of visual analytics has been proposed to help users' visual data analysis and decision-making. Since 2006 when the first symposium of visual analytics was held, the visual analytics research has become popular as the advanced technology in computer graphics, data mining, and human-computer interaction has been incorporated in visual analytics. In this work we introduce the visual analytics research by reviewing and surveying the papers published in IEEE VAST 2015 in terms of data and visualization techniques to help domestics researchers' understanding on visual analytics.

A Case Study on Job Competence Evaluation for the A Course Based on NCS Using VA(Visual Analytics) (VA를 활용한 NCS 기반 교과목의 직무능력평가 사례 연구)

  • Choi, seok-hyun
    • Proceedings of the Korea Contents Association Conference
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    • pp.369-370
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    • 2017
  • 본 연구는 VA(Visual Analytics: 시각적 분석방법)을 활용하여 NCS 기반 교과목 운영에 따른 직무능력평가의 적합성 여부를 밝히고 수행준거별 직무능력 평가 유형의 분석 자료를 시각적으로 제시하고자 하였다.

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Visual Analytics Approach for Performance Improvement of predicting youth physical growth model (청소년 신체 성장 예측 모델의 성능 향상을 위한 시각적 분석 방법)

  • Yeon, Hanbyul;Pi, Mingyu;Seo, Seongbum;Ha, Seoho;Oh, Byungjun;Jang, Yun
    • Journal of The Korea Computer Graphics Society
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    • v.23 no.4
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    • pp.21-29
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    • 2017
  • Previous visual analytics researches has focused on reducing the uncertainty of predicted results using a variety of interactive visual data exploration techniques. The main purpose of the interactive search technique is to reduce the quality difference of the predicted results according to the level of the decision maker by understanding the relationship between the variables and choosing the appropriate model to predict the unknown variables. However, it is difficult to create a predictive model which forecast time series data whose overall trends is unknown such as youth physical growth data. In this paper, we pro pose a novel predictive analysis technique to forecast the physical growth value in small pieces of time series data with un certain trends. This model estimates the distribution of data at a particular point in time. We also propose a visual analytics system that minimizes the possible uncertainties in predictive modeling process.

A Visual Analytics System for Analyzing Social Networking Patterns among Microbloggers (마이크로블로그 사용자의 소셜 네트워킹 패턴 분석 및 가시화 시스템)

  • Koo, Yun-Mo;Lee, Jeong-Jin;Seo, Jin-Wook
    • Journal of Korea Game Society
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    • v.12 no.3
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    • pp.77-86
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    • 2012
  • In recent years, micro-blogging services such as 'Twitter' and 'Me2day' have rapidly become major social networking services. However, it is difficult to grasp the relationship between a user and his/her friends in these micro-blogging services because they simply list messages between them in chronological order. In this paper, we propose a visual analytics system that can help the user intuitively understand relationships with their friends on micro-blogging services by enabling them to analyze the messages quantitatively, qualitatively and temporally. In the visual analytics system, we also present a tool to provide the user with valuable advices after classifying the changing relation patterns with his/her friends, which in turn contributes to improving relationships with friends. The proposed system was successfully implemented as smartphone applications to show its potential to be a tool for analyses and improvement of social relations in micro-blogging services.

Fast Visualization Technique and Visual Analytics System for Real-time Analyzing Stream Data (실시간 스트림 데이터 분석을 위한 시각화 가속 기술 및 시각적 분석 시스템)

  • Jeong, Seongmin;Yeon, Hanbyul;Jeong, Daekyo;Yoo, Sangbong;Kim, Seokyeon;Jang, Yun
    • Journal of The Korea Computer Graphics Society
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    • v.22 no.4
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    • pp.21-30
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    • 2016
  • Risk management system should be able to support a decision making within a short time to analyze stream data in real time. Many analytical systems consist of CPU computation and disk based database. However, it is more problematic when existing system analyzes stream data in real time. Stream data has various production periods from 1ms to 1 hour, 1day. One sensor generates small data but tens of thousands sensors generate huge amount of data. If hundreds of thousands sensors generate 1GB data per second, CPU based system cannot analyze the data in real time. For this reason, it requires fast processing speed and scalability for analyze stream data. In this paper, we present a fast visualization technique that consists of hybrid database and GPU computation. In order to evaluate our technique, we demonstrate a visual analytics system that analyzes pipeline leak using sensor and tweet data.

Treemapping Work-Sharing Relationships among Business Process Performers (트리맵을 이용한 비즈니스 프로세스 수행자간 업무공유 관계 시각화)

  • Ahn, Hyun;Kim, Kwanghoon Pio
    • Journal of Internet Computing and Services
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    • v.17 no.4
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    • pp.69-77
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    • 2016
  • Recently, the importance of visual analytics has been recognized in the field of business intelligence. From the view of business intelligence, visual analytics aims for acquiring valuable insights for decision making by interactively visualizing a variety of business information. In this paper, we propose a treemap-based method for visualizing work-sharing relationships among business process performers. A work-sharing relationship is established between two performers who jointly participate in a specific activity of a business process and is an important factor for understanding organizational structures and behaviors in a process-centric organization. To this end, we design and implement a treemap-based visualization tool for representing work-sharing relationships as well as basic hierarchical information in business processes. Finally, we evaluate usefulness of the proposed visualization tool through an operational example using XPDL (XML Process Definition Language) process models.

Applying and Evaluating Visualization Design Guidelines for a MOOC Dashboard to Facilitate Self-Regulated Learning Based on Learning Analytics

  • Cha, Hyun-Jin;Park, Taejung
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.6
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    • pp.2799-2823
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    • 2019
  • With the help of learning analytics, MOOCs have wider potential to succeed in learning through promoting self-regulated learning (SRL). The current study aims to apply and validate visualization design guidelines for a MOOC dashboard to enhance such SRL capabilities based on learning analytics. To achieve the research objective, a MOOC dashboard prototype, LM-Dashboard, was designed and developed, reflecting the visualization design guidelines to promote SRL. Then, both expert and learner participants evaluated LM-Dashboard through iterations to validate the visualization design guidelines and perceived SRL effectiveness. The results of expert and learner evaluations indicated that most of the visualization design guidelines on LM-Dashboard were valid and some perceived SRL aspects such as monitoring a student's learning progress and assessing their achievements with time management were beneficial. However, some features on LM-Dashboard should be improved to enhance SRL aspects related to achieving their learning goals with persistence. The findings suggest that it is necessary to offer appropriate feedback or tips as well as to visualize learner behaviors and activities in an intuitive and efficient way for the successful cycle of SRL. Consequently, this study contributes to establishing a basis for the visual design of a MOOC dashboard for optimizing each learner's SRL.

Current Status of Educational Big Data Research (교육 빅데이터 관련 연구 동향)

  • Lee, Eun-young;Park, Do-oung;Choi, In-ong
    • Proceedings of the Korean Society of Computer Information Conference
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    • pp.175-176
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    • 2014
  • 본고에서는 교육 빅데이터의 개념, 가치, 처리 기술 및 분석 방법 등을 탐색하였다. '온라인과 오프라인 교수 학습 활동의 투입, 과정, 산출을 통해 생산되는 국가, 지역, 학교, 교사, 학생 수준의 자료'로 정의할 수 있는 교육 빅데이터는 Hadoop으로 대표되는 분산 컴퓨팅 기술을 통해 효율적으로 처리할 수 있다. 대규모 교육 자료에서 의미있고 유용한 결과를 도출하기 위해 주로 사용되는 분석 방법에는 교육 데이터 마이닝, 학습 분석학과 시각 자료 분석학이 있다. 교육 데이터 마이닝은 학생과 교사, 학교의 다양한 수준에서 자료를 폭넓게 분석하는 측면이 강한 반면에 학습 분석학은 학생 수준에서의 자료 분석에 더 초점을 맞추는 경향이 있으며, 시각 자료 분석학은 자료에 대한 분석 자체보다는 분석 결과를 효과적으로 표현하는 방식에 초점이 주어져 있다.

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Visual Mapping from Time-Table Information to Map (일정도표 정보의 지도기반 가시화 기법)

  • Lee, Seok-Jun;Jung, Gi-Sook;Jung, Seung-Dae;Jung, Soon-Ki
    • 한국HCI학회:학술대회논문집
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    • pp.1155-1160
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    • 2006
  • 다양한 과학 분야와 공학 분야에서는 그들이 다루고 있는 특정한 주제의 정보를 좀 더 신속하고, 명확하게 사용자에게 전달하기 위해서 여러 가지 정보 가시화(information visualization) 기법을 사용한다. 정보를 가시화 할 때는 기본적으로 세 가지 과정을 거치는데, 원천 데이터(raw data)로부터 데이터 모델(data model)로 변환하고, 변환된 데이터 모델을 가시화 구조상(visual structure)에 매핑(mapping)시킨 후 정보화 모델(information model)로 변환하게 된다. 본 논문에서는 특정 행사가 진행되고 있는 건물내부에서 발생하는 시간, 공간적인 정보를 정리한 도표 메타포(table metaphor)를 토대로, 해당 데이터 모델로부터 추출한 다양한 정보를 3 차원 지도로 구성된 정보화 모델 상에 반영하기 위한 방법을 제안하였다. 또한, 정보를 단순히 공간상에 반영하기 보다는 사용자의 관심영역(interest area)에 따른 정보의 공간적 의미에 중점을 두어 3차원 공간상에 표현하였다.

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Multi-scale and Interactive Visual Analysis of Public Bicycle System

  • Shi, Xiaoying;Wang, Yang;Lv, Fanshun;Yang, Xiaohang;Fang, Qiming;Zhang, Li
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.6
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    • pp.3037-3054
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    • 2019
  • Public bicycle system (PBS) is a new emerging and popular mode of public transportation. PBS data can be adopted to analyze human movement patterns. Previous work usually focused on specific scales, and the relationships between different levels of hierarchies are ignored. In this paper, we introduce a multi-scale and interactive visual analytics system to investigate human cycling movement and PBS usage condition. The system supports level-of-detail explorative analysis of spatio-temporal characteristics in PBS. Visual views are designed from global, regional and microcosmic scales. For the regional scale, a bicycle network is constructed to model PBS data, and an flow-based community detection algorithm is applied on the bicycle network to determine station clusters. In contrast to the previous used Louvain algorithm, our method avoids producing super-communities and generates better results. We provide two cases to demonstrate how our system can help analysts explore the overall cycling condition in the city and spatio-temporal aggregation of stations.