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

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TiVEx: Optimized Processing for Time Series visual exploration

TiVEx: Optimized Processing for Time Series Visual Explorati...

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ACS/IEEE International conference on Computer Systems and Applications

作者： Heba Helal Mohamed A. Sharaf Mohammad M. Masud Panos K. Chrysanthis College of Information Technology United Arab Emirates University UAE School of Computing and Information University of Pittsburgh United States of America

To facilitate fast-visual data analysis, there is a need for recommending top-k views with "interesting" insights automatically. However, working with high-dimensional time series data makes the process of view recommendations difficult. The primary obstacle lies in finding an automatic way to generate views with less processing time (efficiency) while still closely aligning with the ground truth (effectiveness). In this paper, we propose TiVEx (Time Series visual exploration), a technique to address this challenge. TiVEx aims to achieve a balance between efficiency and effectiveness in generating view recommendations. Through extensive experiments, we demonstrate significant cost savings achieved by TiVEx, indicating its efficiency. Furthermore, our analysis delves into the exploration of striking the right balance between efficiency and effectiveness.

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Towards a visual Approach for Representing Analytical Provenance in exploration Processes 25

Towards a Visual Approach for Representing Analytical Proven...

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25th International conference Information visualisation (IV) - AI and visual Analytics and data Science

作者： Menin, Aline Cava, Ricardo Dal Sasso Freitas, Carla Maria Corby, Olivier Winckler, Marco Univ Cote dAzur CNRS INRIA I3S UMR 7271 Sophia Antipolis France Sul Rio Grandense Fed Inst Pelotas RS Brazil Univ Fed Rio Grande do Sul Inst Informat Porto Alegre RS Brazil

ISBN: (纸本)9781665438278

visualization techniques are useful tools to explore data by enabling the discovery of meaningful patterns and causal relationships. The discovery process is often exploratory and requires multiple views to support analyzing different or complementary perspectives to the data. In this context, analytic provenance shows great potential to understand users' reasoning process through the study of their interactions on multiple view systems. In this paper, we present an approach based on the concept of chained views to support the incremental exploration of large, multidimensional datasets. Our goal is to provide visual representation of provenance information to enable users to retrace their analytical actions and to discover alternative exploratory paths without loosing information on previous analyses. We demonstrate that our implementation of the approach, MGExplorer (Multidimensional Graph Explorer), allows users to explore different perspectives to a dataset by modifying the input graph topology, choosing visualization techniques, arranging the visualization space in meaningful ways to the ongoing analysis and retracing their analytical actions. MGExplorer combines multiple visualization techniques and visual querying while representing provenance information as segments connecting views, which each supports selection operations that help define subsets of the current dataset to be explored by a different view. We demonstrate the usage of the tool through a study case where we explore co-authorship data. We assess the approach through performance metrics, temporal ordering of tasks, number of physical actions, and amount of information to be recalled in-between actions applied to the chosen visual exploration scenarios using chained views.

关键词： Analytical provenance Multiple views Chained views Multidimensional data exploration Provenance visualization

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Mondrian Abstraction and Language Model Embeddings for Differential Pathway analysis

Mondrian Abstraction and Language Model Embeddings for Diffe...

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2024 IEEE International conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Abir, Fuad Al Chen, Jake Y. University of Alabama at Birmingham Department of Computer Science BirminghamAL35233 United States School of Medicine BirminghamAL35233 United States

ISBN: (纸本)9798350386226

In this study, we introduce the Mondrian Map, an innovative visualization tool inspired by Piet Mondrian's abstract art, to address the complexities inherent in visualizing biological networks. The Mondrian Map enables clear and meaningful representations of biological pathways by converting intricate biological data into a structured and intuitive format, facilitating a deeper understanding of molecular dynamics. Each pathway is represented by a square whose size corresponds to fold change, with color indicating the direction of regulation (up or down) and statistical significance. The spatial arrangement of pathways is derived from language model embeddings, preserving neighborhood relationships and enabling the identification of clusters of related pathways. Additionally, colored lines highlight potential crosstalk between pathways, with distinctions between short- and long-range functional interactions. In a glioblastoma multiforme (GBM) case study, the Mondrian Map effectively revealed distinct pathway patterns across patient profiles at different stages of disease progression. By surpassing traditional enriched pathway tables and presenting pathways in a relative context without causing visual information overload, this work highlights the tool's potential to enhance downstream bioinformatics analyses by providing a more comprehensive and visually accessible overview of pathway interactions, offering new avenues for therapeutic exploration and personalized medicine. © 2024 IEEE.

关键词： Cell culture

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Beyond visuals : Examining the Experiences of Geoscience Professionals With Vision Disabilities in Accessing data visualizations

Beyond Visuals : Examining the Experiences of Geoscience Pro...

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IEEE visualization conference (VIS)

作者： Cherukuru, Nihanth W. Bailey, David A. Fourment, Tiffany Hatheway, Becca Holland, Marika M. Rehme, Matt Univ Corp Atmospheric Res UCAR Natl Ctr Atmospher Res NCAR Boulder CO 80307 USA

ISBN: (数字)9781665488129

ISBN: (纸本)9781665488129

data visualizations are ubiquitous in all disciplines and have become the primary means of analysing data and communicating insights. However, the predominant reliance on visual encoding of data continues to create accessibility barriers for people who are blind/vision impaired resulting in their under representation in Science, Technology, Engineering and Mathematics (STEM) disciplines. This research study seeks to understand the experiences of professionals who are blind/vision impaired in one such STEM discipline (geo-sciences) in accessing data visualizations. In-depth, semi-structured interviews with seven professionals were conducted to examine the accessibility barriers and areas for improvement to inform accessibility research pertaining to data visualizations through a socio-technical lens. A reflexive thematic analysis revealed the negative impact of visualizations in influencing their career path, lack of data exploration tools for research, barriers in accessing works of peers and mismatched pace of visualization and accessibility research. The article also includes recommendations from the participants to address some of these accessibility barriers.

关键词： Human-centered computing visualization visualization Design and evaluation methods Human-centered computing Accessibility Accessibility technologies

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PCAPFunnel: A Tool for Rapid exploration of Packet Capture Files 25

PCAPFunnel: A Tool for Rapid Exploration of Packet Capture F...

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25th International conference Information visualisation (IV) - AI and visual Analytics and data Science

作者： Uhlar, Juraj Holkovic, Martin Rusnak, Vit Flowmon Networks Brno Czech Republic Brno Univ Technol Fac Informat Technol Brno Czech Republic Masaryk Univ Inst Comp Sci Brno Czech Republic

ISBN: (纸本)9781665438278

Analyzing network traffic is one of the fundamental tasks in both network operations and security incident analysis. Despite the immense efforts in workflow automation, an ample portion of the work still relies on manual data exploration and analytical insights by domain specialists. Current state-of-the-art network analysis tools provide high flexibility at the expense of usability and have a steep learning curve. Recent-often web-based-analytical tools emphasize interactive visualizations and provide simple user interfaces but only limited analytical support. This paper describes the tool that supports the analytical work of network and security operators. We introduce typical user tasks and requirements. We also present the filtering funnel metaphor for exploring packet capture (PCAP) files through visualizations of linked filter steps. We have created PCAPFunnel, a novel tool that improves the user experience and speeds up packet capture data analysis. The tool provides an overview of the communication, intuitive data filtering, and details of individual network nodes and connections between them. The qualitative usability study with nine domain experts confirmed the usability and usefulness of our approach for the initial data exploration in a wide range of tasks and usage scenarios, from educational purposes to exploratory network data analysis.

关键词： data analysis data visualization Network traffic analysis Packet captures

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Public Outlook on E-sports in China: A Content and Sentiment analysis of Social Media 23

Public Outlook on E-sports in China: A Content and Sentiment...

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23rd IEEE International conference on Information Reuse and Integration for data Science (IEEE IRI)

作者： Wang, Yifan Zheng, Xiaochuan Fan, Tianda Wuhan Univ Sch Informat Management Wuhan Peoples R China Wuhan 39 Middle Sch Grade 11 Wuhan Peoples R China

ISBN: (数字)9781665466035

ISBN: (纸本)9781665466035

This paper aims to help people better understand the Chinese public outlook towards e-sports through the calculation and visual analysis of social media big data, so as to provide reference for the development of e-sports industry and relevant decisions. A mixed-method approach is employed to analyze social media texts by combining quantitative sentiment analysis with qualitative topic and keyword analysis. We have completed the topic coding table of public outlook to e-sports and analyzed the topic distribution and trend. We also have carried out keyword extraction and sentiment calculation for each topic to understand their main contents and sentiment changes. The results show that the Chinese public are paying more and more attention to e-sports and they care about E-sports Profession and E-sports Competition most. Especially, discussions on E-sports Culture show a trend of diversified, profound and normalized development. Combined with keyword analysis and sentiment analysis, it's indicated that people are trying to revise their past recognition of e-sports, but it is still closely related to games in the eyes of the public. Besides, people's sentiment towards the e-sports topics has changed from doubt to recognition, and tends to be stable, while they are more willing to exploration on the e-sports education system, e-sports professionalization and the combination between e-sports and traditional sports.

关键词： e-sports social media topic coding keyword analysis sentiment analysis

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EuroVis 2022 - 24th Eurographics conference on visualization 2022, Posters

EuroVis 2022 - 24th Eurographics Conference on Visualization...

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24th Eurographics conference on visualization, EuroVis 2022

ISBN: (纸本)9783038681854

The proceedings contain 34 papers. The topics discussed include: scientific convergence and divergence in visualization and visual analytics;digital twins of smart farms;automatic segmentation of tooth images: optimization of multi-parameter image processing workflow;explorative visual analysis of spatio-temporal regions to detect hemodynamic biomarker candidates;visually explaining publication ranks in citation-based literature search with PURE suggest;visualizing the evolution of multi-agent game-playing behaviors;visual exploration of genetic sequence variants in pangenomes;interactive visualization of machine learning model results predicting infection risk;a design space for explainable ranking and ranking models;visual queries on bipartite multivariate dynamic social networks;validating perception of hyperspectral textures in virtual reality systems;situated visualization in motion for video games;and using data comics to enhance visualization literacy.

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Construction and Application of Multi-modal Knowledge Graph for Collection of Cultural Relics 2

Construction and Application of Multi-modal Knowledge Graph ...

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2nd International conference on Image Processing and Media Computing, ICIPMC 2023

作者： Liu, Bowei Zhao, Wanqing Wang, Jun Yan, Jing Peng, Jinye Northwest University Xi'an China Shaanxi Academy of Archaeology Xi'an China

ISBN: (纸本)9798350326611

In recent years, computer technology has advanced significantly and more and more museums have begun to prioritize digital protection of cultural relics, achieving fruitful results. However, the digital resources of these relics are often stored in document or relational database forms, and displayed on the museum website using basic division methods. Moreover, each cultural relic collection holds its own unique knowledge points and there must be rich associations between them due to certain commonalities, which cannot be fully applied by existing preservation techniques. Multi-modal Knowledge Graphs (MMKG) have undergone years of development and have achieved significant results and widespread applications. Although China has abundant multi-modal data on cultural relics, there is limited exploration of MMKG in the field of cultural relics. Therefore, this paper proposes to construct a MMKG for museum relics, RelicMMKG, to mine the information contained in the multimodal digital resources of museum relics. This includes using the BERT-BiLSTM-CRF model to identify multiple types of entities in the relic text introduction and using image descriptors to extract and calculate the similarity of visual features in the relic image data. Furthermore, based on the RelicMMKG and structured text and image data, a multifunctional application system is implemented to better explore the correlation between cultural relics, enabling efficient excavation and application of cultural relics data in the museum. © 2023 IEEE.

关键词： Modal analysis

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Metrology and visual analysis Based on the Development Trend of Discipline Research in Colleges and Universities Promote the Discipline Service 2021

Metrology and Visual Analysis Based on the Development Trend...

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2nd International conference on Education Development and Studies (ICEDS)

作者： Wang, Yuenan Lou, Xiaona Han, Xuedan Wei, Danmei Liu, Hongbin Tianjin Univ Res Support Ctr Tianjin Univ Lib Tianjin 300350 Peoples R China

ISBN: (纸本)9781450389617

Through the methods of Metrology and visualization analysis, the paper reveals the papers published by the School of Pharmaceutical Science and Technology of Tianjin University in 2010-2019, reflects the development trend and research hotspot of the discipline research of the school. Based on a variety of data and tools used in Web of Science, Incites and ESI to evaluate scientific research performance, this paper makes a quantitative statistical analysis on the papers, cooperative institutions, research fields and funds. The software of CiteSpace is used to draw the knowledge map and visual analysis of high-frequency keywords is conducted.

关键词： Development Trend Metrology visual analysis CiteSpace Discipline Service

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visual Analytics and exploration of Calcium Transient Imaging data using Event-Based Clustering

Visual Analytics and Exploration of Calcium Transient Imagin...

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IEEE International conference on Big data

作者： Shiaofen Fang Michal Lange Haoying Fu Yingying Chen Yaoying Ma Luddy School of Informatics Computing and Engineering Indiana University Indianapolis IN USA Department of Computer & Information Science Purdue University Indianapolis Department of Pharmacology and Toxicology School of Medicine Indiana University Indianapolis IN USA Department of Pharmacology and Toxicology Stark Neuroscience Institute School of Medicine Indiana University Indianapolis IN USA

Advances in imaging technology and fluorescent calcium indicators have increased the popularity of the application of miniature microscopes (miniscope) in freely-moving rodents when they are performing sophisticated behaviors. The recently established analysis tools, such as Minian, allow for the efficient extraction of neuronal calcium transients from raw videos. However, there is still a gap in front of neuroscientists to draw any conclusions based on the neuronal calcium signals detected during behavioral tests. The poor signal-to-noise ratio and unreliable neuron registration in miniscope images bring significant challenges to the data analysis tasks. This paper describes a visual analytics approach to the exploration of potential neuronal clustering based on the calcium signals and the behavioral tasks. This new interactive solution can be applied for the analysis and exploration of the correlations between calcium imaging data and addiction behavioral data using a combination of visualization, user interaction, visual clustering, and event-related feature selection techniques. The associated interactive software tool is designed to help neuroscientists develop neurobiological hypotheses underlying both physiological and pathological behaviors, which could be a milestone in the field of neuroscience to understanding behavioral coding in the brain at the neuronal level.

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