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检索条件"任意字段=2020 Conference on Visualization and Data Analysis, VDA 2020"

共 2340 条记录，以下是1-10 订阅

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Enhancing Drug Reviews Insights through Exploratory data analysis and Sentiment analysis 28

Enhancing Drug Reviews Insights through Exploratory Data Ana...

引用

28th International conference on Information Visualisation (IV)

作者： Pinto, Ana Sofia Pato, Matilde Datia, Nuno Politecn Lisboa Lisbon Sch Engn ISEL P-1959007 Lisbon Portugal Univ Lisbon IBEB Fac Ciencias P-1749016 Lisbon Portugal Univ Lisbon LASIGE Fac Ciencias P-1749016 Lisbon Portugal NOVA Sch Sci & Technol NOVA LINCS P-2829516 Largo Da Torre Caparica Portugal

ISBN: (纸本)9798350380170;9798350380163

The increasing volume of user-generated content across various online platforms has created vast datasets in multiple domains, including healthcare. This article explores the significant roles of data visualisation and sentiment analysis within the healthcare sector using the UCI ML Drug Review dataset. Our study highlights the value of exploratory data analysis and sentiment analysis in comprehending patient feedback, enriching insights from the dataset. data visualisation effectively elucidates the data's distribution and key characteristics, while sentiment analysis, performed using TextBlob and VADER, categorises the emotional tone of patient reviews. Our methodology aims to provide a deeper understanding of patient satisfaction and medication efficacy based on user-generated content.

关键词： NLP Sentiment analysis Exploratory data analysis Drug Recommendation System Healthcare Support

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Understanding Massive Text visualization 15

Understanding Massive Text Visualization

引用

15th IEEE/ACM Annual International conference on Advances in Social Networks analysis and Mining (ASONAM)

作者： Voltoline, Giovana Pais, Sebastiao Silva, Bruno Cordeiro, Joao Univ Beira Interior Comp Sci Dept Covilha Portugal Univ Beira Interior Covilha Portugal NOVA LINCS Covilha Portugal Univ Beira Interior Inst Telecommun Covilha Portugal Univ Beira Interior INESC TEC Porto Covilha Portugal

ISBN: (纸本)9798400704093

Massive text visualization is a burgeoning field that addresses the visualization, exploration, and analysis of extensive textual datasets, encompassing various domains such as social media, scientific literature, news articles, and more. This paper overviews recent advances, challenges, and potential solutions in massive text visualization and systematically categorizes these works, focusing on shared characteristics such as objectives, preprocessing techniques, processing approaches, and visualization methods. This comprehensive analysis can better understand the current and emerging trends in massive text visualization.

关键词： Massive Text Text visualization Textual data

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analysis and visualization of Stock data Based on LSTM Neural Networks 24

Analysis and Visualization of Stock Data Based on LSTM Neura...

引用

2024 International conference on Intelligent Education and Computer Technology, IECT 2024

作者： Deng, Chao Yuan, Bo College of Computer Guangdong University of Science and Technology Dongguan China

ISBN: (纸本)9798400709920

This paper explores the analysis and visualization of stock data based on LSTM neural networks. Taking Ping An Bank's stock data from January 1, 2020, to April 30, 2024, as a case study. Through data acquisition, visualization analysis, correlation analysis, data processing, and modeling, the prediction problem of stock closing prices is explored. In the model construction, the Pandas library in Python is used for data processing and visualization, and the Keras interface in TensorFlow is used to implement the LSTM neural network model. By comparing the prediction accuracy of SGD and Adam optimization algorithms under different learning rates through experiments, and analyzing their performance and stability in depth, the results show that the LSTM neural network model optimized by Adam algorithm with a learning rate of 0.001 has higher prediction accuracy. This discovery can provide certain reference value for the prediction of stock market closing prices. © 2024 ACM.

关键词： data accuracy

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Proceedings of the 14th IADIS International conference Computer Graphics, visualization, Computer Vision and Image Processing 2020, CGVCVIP 2020 and Proceedings of the 5th IADIS International conference Big data Analytics, data Mining and Computational Intelligence 2020, BigDaCI 2020 and Proceedings of the 9th IADIS International conference Theory and Practice in Modern Computing 2020, TPMC 2020 - Part of the 14th Multi conference on Computer Science and Information Systems, MCCSIS 2020

Proceedings of the 14th IADIS International Conference Compu...

引用

14th IADIS International conference Computer Graphics, visualization, Computer Vision and Image Processing 2020, CGVCVIP 2020 and 5th IADIS International conference Big data Analytics, data Mining and Computational Intelligence 2020, BigDaCI 2020 and 9th IADIS International conference Theory and Practice in Modern Computing 2020, TPMC 2020, Part of the 14th Multi conference on Computer Science and Information Systems, MCCSIS 2020

ISBN: (纸本)9789898704214

The proceedings contain 35 papers. The topics discussed include: data-driven approach for generating colormaps of scientific simulation data;a 3D-shockwave volume rendering algorithm based on feature boundary detection;using reorderable matrices to compare risk curves of representative models in oil reservoir development and management activities;laser spot detection and characteristic analysis in plasma interaction simulation;hybrid sort a pattern-focused matrix reordering approach based on classification;data interpolation based on contextual analysis for generating tomographic images in concrete specimen;graphical user interface personalization: user study of image frequency preferences;evaluation of color spaces for unsupervised and deep learning skin lesion segmentation;and repeated pattern extraction with knowledge-based attention and semantic embeddings.

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Towards Contextual Glyph Design: Visualizing Hearing Screenings 27

Towards Contextual Glyph Design: Visualizing Hearing Screeni...

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27th International conference on Information Visualisation (IV) / 19th International conference Computer Graphics, Imaging and visualization (CGiV)

作者： Ramos, Barbara Nascimento Macas, Catarina Lourenco, Nuno Polisciuc, Evgheni Univ Coimbra Dept Informat Engn CISUC Coimbra Portugal

ISBN: (纸本)9798350341614

data is everywhere, our society shapes itself through it and, with the years passing by, it is becoming greater in dimension. A lot of this data now available is multivariate in nature. The bigger the volume and complexity are, the harder tasks to detect, classify, and measure characteristics and relations within data. Glyph-based visualization is one of the possible techniques commonly adopted in data science to address the representation of multivariate data. Multiple varieties of glyph design have been developed and studied over the past decades. However, little research was done to compare the effectiveness of glyphs designs developed for a specific context of the application. This paper aims to study data glyphs and their applications. More specifically, three visual explorations are produced as glyph design alternatives to represent a dataset related to audiological tests carried out in the population of Portugal. These glyphs were evaluated through controlled semi-structured experiments with users, and a crowdsourced experiment, and then an analysis of the performance result of each of the glyphs is presented, evaluating them in terms of learning and memorization. The results show how the use of metaphors and semantic relations to represent the attributes helps in understanding the glyph and its memorization. Additionally, we identified that the redundancy in encoding data might be beneficial.

关键词： data glyphs design Glyph-based visualization Multivariate data visualization

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Sub-system Integration and Health Dashboard for Autonomous Mobile Robots 3rd

Sub-system Integration and Health Dashboard for Autonomous M...

引用

3rd International conference on Optimization, Learning Algorithms and Applications (OL2A)

作者： Franca, Andre Loures, Eduardo Jorge, Luisa Mendes, Andre Inst Politecn Braganca IPB Braganca Portugal Univ Tecnol Fed Parana UTFPR Curitiba Parana Brazil

ISBN: (纸本)9783031530357;9783031530364

data visualization has become increasingly important to improve equipment monitoring, reduce operational costs and increase process efficiency with the ever-increasing amount of data being generated and collected in various fields. This paper proposes the development of a health monitoring system for an Autonomous Mobile Robot (AMR) that allows data acquisition and analysis for decision-making. The implementation of the proposed system showed favourable results in data acquisition, analysis, and visualization for decision-making. Through the use of a hybrid control architecture, the data acquisition and processing demonstrated efficiency without significant impact on battery consumption or resource usage of the AMR embedded microcomputer. The developed dashboard proved to be efficient in navigating and visualizing the data, providing important tools for the platform manager's decision-making. This work contributes to the health monitoring of devices based on Robot Operating System (ROS), which may be of interest to professionals and researchers in fields related to robotics and automation. Furthermore, the system presented will be open source, making it accessible and adaptable for use in different contexts and applications.

关键词： Human Machine Interface data visualization Autonomous Mobile Robot Robot Operating System Open Source Software

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VOILA 2020 - Proceedings of the 5th International Workshop on visualization and Interaction for Ontologies and Linked data, co-located with the 19th International Semantic Web conference, ISWC 2020

VOILA 2020 - Proceedings of the 5th International Workshop o...

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5th International Workshop on visualization and Interaction for Ontologies and Linked data, VOILA 2020

The proceedings contain 7 papers. The topics discussed include: a comparative study of state-of-the-art linked data visualization tools;user-centered design for knowledge imbalance analysis: a case study of ProWD;towards designing a tool for understanding proofs in ontologies through combined node-link diagrams;a real-time visual dashboard for wikidata edits;LogVis: graph-assisted visual analysis of event logs from industrial equipment;and the semantic combining for exploration of environmental and disease data dashboard for clinician researchers.

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Bibliometric analysis and Systematic Literature Review on data visualization 14th

Bibliometric Analysis and Systematic Literature Review on Da...

引用

14th International conference on Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management (DHM) Held as Part of the 25th International conference on Human-Computer Interaction (HCII)

作者： Kim, Byeongmok Kim, Yonggab Duffy, Vincent G. Purdue Univ W Lafayette IN 47907 USA

ISBN: (纸本)9783031357473;9783031357480

This study aims to investigate the literature review as a job and explore the research trend of data visualization. This study used various methods to perform a systematic literature review on data visualization. Metadata was abstracted from well-known research databases such as SCOPUS, Google Scholar, and Web of Science. The metadata was used for analysis by VOSviewer, MAXQDA, BibExcel, and Citespace. In conclusion, we discuss the research trend and anticipated future studies on data visualization.

关键词： data visualization Job design Human Factor Human Computer Interaction

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Interactive Visual analysis of COVID-19 28

Interactive Visual Analysis of COVID-19

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28th International conference on Information Visualisation (IV)

作者： Varga, Margaret Ndoni, Adelica Traeber-Burdin, Susan Panganiban, April Rose Lavigne, Valerie Univ Oxford Dept Biol Oxford England NATO Commun & Informat Agcy NCIA The Hague Netherlands Fraunhofer FKIE Human Machine Syst Bonn Germany Air Force Res Lab Dayton OH USA Def Res & Dev Canada Valcartierr PQ Canada

ISBN: (纸本)9798350380170;9798350380163

COVID-19 is an infectious disease caused by the SARS-CoV-2 virus. It was first detected in China in December 2019. It spreads between people in close contact. On the 11(th) March 2020 the WHO declared the outbreak of the virus as a pandemic, which signaled a significant acceleration in the global response to the COVID-19 outbreak, and recognized the widespread transmission of the virus across multiple countries and continents. data regarding COVID-19 was gathered and made available for open access. These data sources offer invaluable information for tracking, raising awareness and understanding of COVID-19, recognizing its impact, as well as informing the general public, health authorities, policy makers, situation managers and decision makers. However, COVID-19 data in its raw form is complex and difficult to understand and analyze. The application of visualization together with human factor design principles in a complex systems framework provides an effective means for exploiting these big and complex datasets. These techniques can transform such inherently non-visual data into intuitive visual forms that enable users to gain insight into, and understanding of, information contained within the data. This paper discusses the application of visualization and development of interactive dashboards, set in a complex systems framework, to provide an effective means for the users to explore, analyze and gain awareness of the situation, thus enabling informed decision making.

关键词： COVID-19 visualization complex systems human factors visual analytics

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Advanced visualization of adaptive optics telemetry data 9

Advanced visualization of adaptive optics telemetry data

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conference on Adaptive Optics Systems IX

作者： Silva, Beatriz Gomes, Tiago Correia, Carlos M. Garcia, Paulo J., V Univ Porto Fac Engn Rua Dr Roberto Frias S-N P-4200465 Porto Portugal Inst Super Tecn Ctr Astrophys & Gravitat Ave Rovisco Pais 1 P-1049001 Lisbon Portugal

ISBN: (纸本)9781510675186;9781510675179

The Adaptive Optics Telemetry (AOT) format has recently been proposed to standardize the telemetry data generated by adaptive optics systems. Yet its usability remains limited by the user's programming expertise and familiarity with the accompanying Python package. There is an opportunity for substantial improvement in data accessibility by offering users an alternative tool for conducting exploratory data analysis in a visual and intuitive manner. We aim to design and develop an open-source Python visualization tool for exploring AOT data. This tool should support researchers and users by offering a broad set of interactive features for the analysis and exploration of the data. We designed a prototype dashboard and performed user testing to validate its usability. We compared the prototype with existing data visualization and exploration tools to ensure we provided the necessary functionality. We made publicly available a user-friendly dashboard for analyzing and exploring AOT data.

关键词： Adaptive Optics Telemetry visualization Dashboard

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