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检索条件"任意字段=Conference on Visual Data Exploration and Analysis IV"

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Exploring Time-Series Through Force-Directed Timelines 24

Exploring Time-Series Through Force-Directed Timelines

引用

24th International conference Information visualisation (iv)

作者： Cruz, Antonio Arrais, Joel P. Machado, Penousal Univ Coimbra CISUC Dept Informat Engn Coimbra Portugal

ISBN: (纸本)9781728191348

Temporal datasets are a product of many scientific disciplines and analyzing the events that they describe may help provide valuable insight into their respective research subjects and help move towards solutions to existing problems. Time-series analysis is still an open problem which prompts new solutions, particularly the discovery of patterns across complex temporal networks. visualization has proven to be a valuable tool in the analysis of such datasets, with the emergence of new models such as Time Curves, which distorts timelines to position time points based on their similarity, creating visualizations that highlight behavior patterns. In this paper, we further explore time-series functionally and aesthetically by revising the dynamic Time Curves models in CroP, a visualization tool with coordinated multiple views. Firstly, we propose the additional of new visual elements and interactive functions, coordinated with a network visualization to help discover and understand temporal patterns across complex datasets. Secondly, we visually explore time-series through Time Paths, a parameter-based force-directed layout that can dynamically transform the original model to either highlight small data variations or reduce visual noise in favor of overall patterns.

关键词： data visualization Time series analysis Interactive systems

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visual analysis of interactive document clustering streams 20

Visual analysis of interactive document clustering streams

引用

Working conference on Advanced visual Interfaces (AVI)

作者： Cabral, Eric M. Milios, Evangelos E. Minghim, Rosane Univ Sao Paulo Sao Carlos SP Brazil Dalhousie Univ Halifax NS Canada Univ Coll Cork Cork Ireland

ISBN: (纸本)9781450375351

Interactive clustering techniques play a key role by putting the user in the clustering loop, allowing her to interact with document group abstractions instead of full-length documents. It allows users to focus on corpus exploration as an incremental task. To explore Information Discovery's incremental aspect, this article proposes a visual component to depict clustering membership changes throughout a clustering iteration loop in both static and dynamic data sets. The visual component is evaluated with an expert user and with an experiment with data streams.

关键词： Document clustering visual analytics Document streams Text visualization

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Locating Embodied Forms of Urban Wayfinding: An exploration 16th

Locating Embodied Forms of Urban Wayfinding: An Exploration

引用

16th International conference on Diversity, Divergence, Dialogue, iconference 2021

作者： Noone, Rebecca University of Toronto Toronto Canada

ISBN: (纸本)9783030712914

The following short paper looks at the embodied information practice of urban wayfinding in the context of pervasive locative media and mobile mapping technology. The author asks: what informational cues are encoded in the urban landscape and activated through embodied practices of wayfinding? To explore this question of street-level wayfinding, the author utilizes the exploratory method of arts-based research, focusing on the act of giving directions, both spoken and drawn, and developing the research in four unique cities: Amsterdam, London, New York, and Toronto. analysis of the data uses visual grounded theory and situational analysis. Based on the findings, the author classifies three types of urban forms that helped guide navigation during these wayfinding encounters: pathways, transmitters, and markings. In unpacking the variants within these registers of spatial sense-making, the author identifies informational elements of the city present in its material and built environment but also in its social and tacit forms. The paper offers a framework to look at the multiplicities of information, structured and embodied, that guide wayfinding, situated beyond (but co-existent with) mobile mapping tools. © 2021, Springer Nature Switzerland AG.

关键词： Arts-based methods Embodied information practices Urban wayfinding

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Towards a Conceptual Model for data Narratives 39th

Towards a Conceptual Model for Data Narratives

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39th International conference on Conceptual Modeling (ER)

作者： El Outa, Faten Francia, Matteo Marcel, Patrick Peralta, Veronika Vassiliadis, Panos Univ Tours Blois Loir & Cher France Univ Ioannina Ioannina Greece Univ Bologna Cesena Italy

ISBN: (纸本)9783030625221;9783030625214

data narration is the activity of producing stories supported by facts extracted from data analysis, possibly using interactive visualizations. In spite of the increasing interest in data narration in several communities (e.g. journalism, business, e-government), there is no consensual definition of data narrative, let alone a conceptual or logical model of it. In this paper, we propose a conceptual model of data narrative for exploratory data analysis. It is based on four layers that reflect the transition from raw data to the visual rendering of the data story: factual, intentional, structural and presentational. This model aims to support the entire lifecycle of building a data narrative, starting from an intentional goal: fetch and explore data, bring out highlights, derive important messages, structure the plot of the data narrative, and render it in a visual manner. Our contributions include a description of the model and its instantiation for several real examples showing that it covers data narration needs.

关键词： data narrative visual narrative data storytelling data exploration

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ICDAR 2021 Competition on Components Segmentation Task of Document Photos 16th

ICDAR 2021 Competition on Components Segmentation Task of Do...

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16th IAPR International conference on Document analysis and Recognition (ICDAR)

作者： Lopes Junior, Celso A. M. das Neves Junior, Ricardo B. Bezerra, Byron L. D. Toselli, Alejandro H. Impedovo, Donato Univ Pernambuco Polytech Sch Pernambuco Recife PE Brazil Univ Politecn Valencia PRHLT Res Ctr Cami Vera S-N Valencia Spain Univ Bari Dept Comp Sci Bari Italy

ISBN: (纸本)9783030863371;9783030863364

This paper describes the short-term competition on "Components Segmentation Task of Document Photos" that was prepared in the context of the "16th International conference on Document analysis and Recognition" (ICDAR 2021). This competition aims to bring together researchers working on the filed of identification document image processing and provides them a suitable benchmark to compare their techniques on the component segmentation task of document images. Three challenge tasks were proposed entailing different segmentation assignments to be performed on a provided dataset. The collected data are from several types of Brazilian ID documents, whose personal information was conveniently replaced. There were 16 participants whose results obtained for some or all the three tasks show different rates for the adopted metrics, like "Dice Similarity Coefficient" ranging from 0.06 to 0.99. Different Deep Learning models were applied by the entrants with diverse strategies to achieve the best results in each of the tasks. Obtained results show that the current applied methods for solving one of the proposed tasks (document boundary detection) are already well stablished. However, for the other two challenge tasks (text zone and handwritten sign detection) research and development of more robust approaches are still required to achieve acceptable results.

关键词： ID document images visual object detection and segmentation Processing of identification document images

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JobViewer: Graph-based visualization for Monitoring High-Performance Computing System

JobViewer: Graph-based Visualization for Monitoring High-Per...

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IEEE/ACM International Symposium on Big data Computing (BDC)

作者： Tommy Dang Ngan V.T. Nguyen Jie Li Alan Sill Jon Hass Yong Chen Department of Computer Science Texas Tech University Lubbock Texas USA High Performance Computing Center Texas Tech University Lubbock Texas USA Dell Inc Austin Texas USA

visualization aims to strengthen data exploration and analysis, especially for complex and high-dimensional data. High-performance computing (HPC) systems are typically large and complicated instruments that generate massive performance and operation time series. Monitoring HPC systems’ performance is a daunting task for HPC admins and researchers due to their dynamic natures. This work proposes a visual design using the bipartite graph’s idea to visualize HPC clusters’ structure, metrics, and job scheduling data. We built a web-based prototype, called JobViewer, that integrates advanced methods in visualization and human-computer interaction (HCI) to demonstrate the benefits of visualization in real-time monitoring HPC centers. We also showed real use cases and a user study to validate the efficiency and highlight the current approach’s drawbacks.

关键词： Human computer interaction visualization High performance computing Source coding Time series analysis data visualization Bipartite graph

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A Language-based Interface for analysis of Digital Storytelling 20

A Language-based Interface for Analysis of Digital Storytell...

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Working conference on Advanced visual Interfaces (AVI)

作者： Gloder, Alberto Ducceschi, Luca Zancanaro, Massimo Univ Trento Dept Psychol & Cognit Sci Rovereto TN Italy Univ Trento FBK Rovereto TN Italy

ISBN: (纸本)9781450375351

In this paper, we introduce a tool aimed at supporting deep qualitative analysis of digital comics. The tool exploits language-based technologies to facilitate the exploration of relatively large sets of comics. The core idea is that the specific words used in the comics are both an important element of the analysis and an index to navigate and explore the dataset. The design concept has been validated in a pilot study and the findings provide evidence that the approach meets the needs of qualitative analysts with the potential of improving their practices.

关键词： data analysis Digital storytelling Comics Machine Learning Natural language processing

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visual Analytics Meets Process Mining: Challenges and Opportunities

Visual Analytics Meets Process Mining: Challenges and Opport...

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International conference on Process Mining (ICPM)

作者： Silvia Miksch Institute of Visual Computing and Human-Centered Technology Vienna University of Technology (TU Wien) Favoritenstraße 9-11/193-07 Vienna Austria

visual Analytics integrates the outstanding capabilities of humans in terms of visual information exploration with the enormous processing power of computers to form a powerful knowledge discovery environment. In other words, visual Analytics is the science of analytical reasoning facilitated by interactive interfaces and captures the information discovery process keeping the human in the loop. Process Mining aims to extract information and knowledge from event logs to discover, monitor, and improve processes in a variety of application domains. Such event data or traces of activities often possess data quality issues as well as exhibit unexpected behavior and complex relations. Consequently, before and during the implementation of interactive (automated or semi-automated) analysis methods, such as Process Mining algorithms, the analyst needs to explore, investigate, and understand the data at hand in order to decide which analysis methods might be appropriate. The combination of interactive visual data analyses and exploration with Process Mining algorithms makes complex information structures more comprehensible and facilitates new insights. In this talk, I will illustrate the concepts of visual Analytics, how visual Analytics combined with Process Mining techniques supports to extract more insights from complex event data, and elaborate about the challenges and opportunities for analyzing process data with visual Analytics methods. Various examples will illustrate what has been achieved so far and show possible future directions and challenges.

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27th International conference on MultiMedia Modeling, MMM 2021

27th International Conference on MultiMedia Modeling, MMM 20...

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27th International conference on MultiMedia Modeling, MMM 2021

ISBN: (纸本)9783030678319

The proceedings contain 50 papers. The special focus in this conference is on MultiMedia Modeling. The topics include: Unsupervised Gaze: exploration of Geometric Constraints for 3D Gaze Estimation;Median-Pooling Grad-CAM: An Efficient Inference Level visual Explanation for CNN Networks in Remote Sensing Image Classification;multi-granularity Recurrent Attention Graph Neural Network for Few-Shot Learning;EEG Emotion Recognition Based on Channel Attention for E-Healthcare Applications;the MovieWall: A New Interface for Browsing Large Video Collections;keystroke Dynamics as Part of Lifelogging;HTAD: A Home-Tasks Activities dataset with Wrist-Accelerometer and Audio Features;MNR-Air: An Economic and Dynamic Crowdsourcing Mechanism to Collect Personal Lifelog and Surrounding Environment dataset. A Case Study in Ho Chi Minh City, Vietnam;kvasir-Instrument: Diagnostic and Therapeutic Tool Segmentation dataset in Gastrointestinal Endoscopy;tropical Cyclones Tracking Based on Satellite Cloud Images: database and Comprehensive Study;catMeows: A Publicly-Available dataset of Cat Vocalizations;search and Explore Strategies for Interactive analysis of Real-Life Image Collections with Unknown and Unique Categories;graph-Based Indexing and Retrieval of Lifelog data;on Fusion of Learned and Designed Features for Video data Analytics;XQM: Interactive Learning on Mobile Phones;a Multimodal Tensor-Based Late Fusion Approach for Satellite Image Search in Sentinel 2 Images;canopy Height Estimation from Spaceborne Imagery Using Convolutional Encoder-Decoder;implementation of a Random Forest Classifier to Examine Wildfire Predictive Modelling in Greece Using Diachronically Collected Fire Occurrence and Fire Mapping data;mobile eHealth Platform for Home Monitoring of Bipolar Disorder;multimodal Sensor data analysis for Detection of Risk Situations of Fragile People in @home Environments.

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27th International conference on MultiMedia Modeling, MMM 2021

27th International Conference on MultiMedia Modeling, MMM 20...

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27th International conference on MultiMedia Modeling, MMM 2021

ISBN: (纸本)9783030678340

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