2017 IEEE Conference on Visual Analytics Science and Technology (VAST)最新文献_第3页

E-Map: A Visual Analytics Approach for Exploring Significant Event Evolutions in Social Media 电子地图:探索社交媒体中重大事件演变的可视化分析方法

2017 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2017-10-01 DOI: 10.1109/VAST.2017.8585638

Siming Chen, Shuai Chen, Lijing Lin, Xiaoru Yuan, Jie Liang, X. Zhang

{"title":"E-Map: A Visual Analytics Approach for Exploring Significant Event Evolutions in Social Media","authors":"Siming Chen, Shuai Chen, Lijing Lin, Xiaoru Yuan, Jie Liang, X. Zhang","doi":"10.1109/VAST.2017.8585638","DOIUrl":"https://doi.org/10.1109/VAST.2017.8585638","url":null,"abstract":"Significant events are often discussed and spread through social media, involving many people. Reposting activities and opinions expressed in social media offer good opportunities to understand the evolution of events. However, the dynamics of reposting activities and the diversity of user comments pose challenges to understand event-related social media data. We propose E-Map, a visual analytics approach that uses map-like visualization tools to help multi-faceted analysis of social media data on a significant event and in-depth understanding of the development of the event. E-Map transforms extracted keywords, messages, and reposting behaviors into map features such as cities, towns, and rivers to build a structured and semantic space for users to explore. It also visualizes complex posting and reposting behaviors as simple trajectories and connections that can be easily followed. By supporting multi-level spatial temporal exploration, E-Map helps to reveal the patterns of event development and key players in an event, disclosing the ways they shape and affect the development of the event. Two cases analysing real-world events confirm the capacities of E-Map in facilitating the analysis of event evolution with social media data.","PeriodicalId":149607,"journal":{"name":"2017 IEEE Conference on Visual Analytics Science and Technology (VAST)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134429647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 32

GC --- Holistic Analysis of Heterogeneous Datasets GC—异构数据集的整体分析

2017 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2017-10-01 DOI: 10.1109/VAST.2017.8585435

Silvana Podaras, Michael Beham, R. Splechtna, D. Gračanin, K. Matkovič

引用次数: 0

A Visual Explorer for Analyzing Trajectory Patterns 用于分析轨迹模式的可视化资源管理器

2017 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2017-10-01 DOI: 10.1109/VAST.2017.8585462

Wooil Kim, Changbeom Shim, Ilhyun Suh, Y. Chung

引用次数: 2

Interactive Visual Analytics Application for Spatiotemporal Movement Data VAST Challenge 2017 Mini-Challenge 1: Award for Actionable and Detailed Analysis 时空运动数据交互式可视化分析应用VAST挑战赛2017迷你挑战赛1:可操作和详细分析奖

2017 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2017-10-01 DOI: 10.1109/VAST.2017.8585564

Yifei Guan, Kam Tin Seong

引用次数: 2

Detecting Vehicular Patterns Using a Graph-Based Approach 使用基于图的方法检测车辆模式

2017 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2017-10-01 DOI: 10.1109/VAST.2017.8585667

Sirisha Velampalli, Lenin Mookiah, W. Eberle

引用次数: 0

VAST Challenge 2017: Mystery at the Wildlife Preserve 2017年浩瀚挑战:野生动物保护区之谜

2017 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2017-10-01 DOI: 10.1109/VAST.2017.8585503

M. Whiting, Kristin A. Cook, R. J. Crouser, John Fallon, G. Grinstein, J. Haack, C. Henderson, Kristen Liggett, D. Staheli, J. Strasburg, J. Tagestad, Carrie Varley

{"title":"VAST Challenge 2017: Mystery at the Wildlife Preserve","authors":"M. Whiting, Kristin A. Cook, R. J. Crouser, John Fallon, G. Grinstein, J. Haack, C. Henderson, Kristen Liggett, D. Staheli, J. Strasburg, J. Tagestad, Carrie Varley","doi":"10.1109/VAST.2017.8585503","DOIUrl":"https://doi.org/10.1109/VAST.2017.8585503","url":null,"abstract":"The VAST Challenge 2017 offered three mini-challenges and a grand challenge dealing with environmental problems potentially caused by human patterns of life and potentially harmful chemically laden effluent plumes being emitted from factory smokestacks. The data provided included traffic patterns, sensor data though a Preserve, information about the Preserve, multispectral imagery and a map to help an ornithology graduate student particularly concerned with the population decrease of the Rose-Crested Blue Pipit determine who and what might be responsible. Mini-Challenge 1 focused on analysis of vehicles passing through the Preserve over time. Mini-Challenge 2 looked at data collected by air sampling monitors surrounding nearby factories, along with meteorological readings, to understand potential impacts they may be having on the Pipit. Mini-Challenge 3 required investigation into several months of multi-spectral imagery over the area to understand the Preserve’s general health. The Grand Challenge asked participants to synthesize across all three mini-challenges to create hypotheses of what is happening and what sensible next steps could be. This year’s challenge received 58 submissions and recorded over 1100 unique downloads from 20 countries prior to the submission deadline.","PeriodicalId":149607,"journal":{"name":"2017 IEEE Conference on Visual Analytics Science and Technology (VAST)","volume":"237 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122503227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

MC3 - A Web-Based Interactive Image Explorer for Temporal Analysis of Satellite Images (Honorable Mention - Good Interactive Image Explorer) MC3 -基于web的交互式图像浏览器，用于卫星图像的时间分析(荣誉奖-良好的交互式图像浏览器)

2017 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2017-10-01 DOI: 10.1109/VAST.2017.8585425

Vijayraj Mahida, Bartosz Kupiec, A. Burks, T. Luciani, G. Marai

引用次数: 1

Pattern Trails: Visual Analysis of Pattern Transitions in Subspaces 模式轨迹:子空间中模式转换的可视化分析

2017 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2017-10-01 DOI: 10.1109/VAST.2017.8585613

Dominik Jäckle, Michael Hund, M. Behrisch, D. Keim, T. Schreck

{"title":"Pattern Trails: Visual Analysis of Pattern Transitions in Subspaces","authors":"Dominik Jäckle, Michael Hund, M. Behrisch, D. Keim, T. Schreck","doi":"10.1109/VAST.2017.8585613","DOIUrl":"https://doi.org/10.1109/VAST.2017.8585613","url":null,"abstract":"Figure 1:Visual analysis of subspace patterns by a series of consecutive pattern transitions between scatterplots. (a) Scatterplots depict subspaces and are grouped and sorted based on similarity. (b) This example shows the pattern transitions in the University data set. Based on a 3D cube like visualization, one can trace sorted patterns in a side and top view on the cube (see Section 7.1).Subspace analysis methods have gained interest for identifying patterns in subspaces of high-dimensional data. Existing techniques allow to visualize and compare patterns in subspaces. However, many subspace analysis methods produce an abundant amount of patterns, which often remain redundant and are difficult to relate. Creating effective layouts for comparison of subspace patterns remains challenging. We introduce Pattern Trails, a novel approach for visually ordering and comparing subspace patterns. Central to our approach is the notion of pattern transitions as an interpretable structure imposed to order and compare patterns between subspaces. The basic idea is to visualize projections of subspaces side-by-side, and indicate changes between adjacent patterns in the subspaces by a linked representation, hence introducing pattern transitions. Our contributions comprise a systematization for how pairs of subspace patterns can be compared, and how changes can be interpreted in terms of pattern transitions. We also contribute a technique for visual subspace analysis based on a data-driven similarity measure between subspace representations. This measure is useful to order the patterns, and interactively group subspaces to reduce redundancy. We demonstrate the usefulness of our approach by application to several use cases, indicating that data can be meaningfully ordered and interpreted in terms of pattern transitions.","PeriodicalId":149607,"journal":{"name":"2017 IEEE Conference on Visual Analytics Science and Technology (VAST)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126458396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 17

Interactive Visual Analysis of Traffic Patterns: Ecological Impact within a Nature Preserve (VAST Challenge 2017) 交通模式的交互式可视化分析:自然保护区内的生态影响(VAST挑战2017)

2017 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2017-10-01 DOI: 10.1109/VAST.2017.8585729

Allison Montroy, Tyler Witter, Christopher Banas, Walter D. Bennette

引用次数: 0

MC3 — Modified Frame Differencing of Satellite Images to Detect Temporal Changes in a Natural Preserve MC3 -改进的卫星图像帧差检测自然保护区的时间变化

2017 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2017-10-01 DOI: 10.1109/VAST.2017.8585476

Michael Beham, R. Splechtna, Silvana Podaras, D. Gračanin, K. Matkovič

引用次数: 0