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

共 1754 条记录，以下是21-30 订阅

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Automated data exploration and analysis 41st

Automated Data Exploration and Analysis

引用

41st Computer Graphics International conference, CGI 2024

作者： Wu, Tong Wang, Song Peng, Xin School of Computer Science and Technology Southwest University of Science and Technology Mianyang China

ISBN: (纸本)9783031820205

The paper presents a recommender algorithm for visual analysis based on data field Schema and Aggregation, and developed an automated data analysis solution recommendation system (AutoEDA) in conjunction with the Exploratory data analysis process (EDA). To address the issue of field type recognition, we designed a dynamic field recognition framework combining four classification models to automatically classify data field types. For the evaluation of analysis strategies, we proposed an analysis strategy evaluation method based on the Chart Attribute Length for designing custom search strategies and defining chart matching rules. Finally, through interactive visual backtracking and the functionality of modifying and tracing analysis solutions, we collaborated with data analysts of varying experience levels, and validated the effectiveness and feasibility of the proposed solution with structured data from publicly available websites. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： data aggregation

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Weedle: Composable Dashboard for data-Centric NLP in Computational Notebooks

Weedle: Composable Dashboard for Data-Centric NLP in Computa...

引用

32nd World Wide Web conference (WWW)

作者： Kwon, Nahyun Kim, Hannah Rahman, Sajjadur Zhang, Dan Hruschka, Estevam Texas A&M Univ College Stn TX 77834 USA Megagon Labs Mountain View CA USA

ISBN: (纸本)9781450394161

data-centric NLP is a highly iterative process requiring careful exploration of text data throughout entire model development life-cycle. Unfortunately, existing data exploration tools are not suitable to support data-centric NLP because of workfow discontinuity and lack of support for unstructured text. In response, we propose Weedle, a seamless and customizable exploratory text analysis system for data-centric NLP. Weedle is equipped with built-in text transformation operations and a suite of visual analysis features. With its widget, users can compose customizable dashboards interactively and programmatically in computational notebooks.

关键词： exploratory data analysis computational notebooks

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Motion Blur Impact on Measurement in Autonomous Inspection 20

Motion Blur Impact on Measurement in Autonomous Inspection

引用

20th IEEE/ASME International conference on Mechatronic and Embedded Systems and Applications (MESA)

作者： Jose, Nahuel Marchello, Gabriele Cannella, Ferdinando Italian Inst Technol Genoa Italy

ISBN: (纸本)9798331516246;9798331516239

This paper investigates the application of mobile robotic platforms for visual data capture in infrastructure inspection tasks. The captured data offer significant value for both manual and automated inspection processes. It can produce detailed visual information for human inspectors and serve as input for automated systems to detect anomalies or assist inspectors through computer-aided analysis. Additionally, these data can be integrated into the robot navigation system for real-time path optimisation. A critical challenge in optimising data capture is highlighted: balancing the desired precision with the time invested in inspections. The study explores this tradeoff by analysing the impact of motion blur on measurement errors. Capturing high-quality images with minimal motion blur necessitates slower inspection speeds. The findings suggest that for extensive inspection areas, prioritising mid-range object distances can optimise data capture, as errors increase at a slower pace at these distances compared to closer or farther ranges. This research paves the way for further advancements. Future areas of exploration include evaluating noise reduction techniques, incorporating real-world complexities into testing environments, and investigating the impact of capture speed on machine learning algorithms.

关键词： Image quality assessment video quality assessment monitoring of structures visual inspection motion blur assessment structural health monitoring (SHM)

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Navigating data Repositories: Utilizing Line Charts to Discover Relevant datasets 50th

Navigating Data Repositories: Utilizing Line Charts to Disco...

引用

50th International conference on Very Large data Bases, VLDB 2024

作者： Ji, Daomin Luo, Hui Bao, Zhifeng Culpepper, Shane RMIT University Australia University of Wollongong Australia The University of Queensland Australia

Line charts are fundamental to data analysis and exploration, offering concise visual representations of trends. However, gaining access to the underlying data used to construct these charts is often challenging. In this paper, we describe DDLC (short for dataset discovery via line charts), an automatic dataset discovery tool that is able to not only identify datasets (from a dataset repository) that are "relevant" to the information depicted from a line chart provided by the users, but also empower users to refine search results based on specific visual elements extracted from the line chart. Moreover, DDLC offers multiple avenues for users to validate search outcomes: 1) Providing explanations on how a similar line chart could be generated from the identified dataset;2) enabling comparison of line charts generated from different datasets via different ways (e.g., the aggregation vs. non-aggregation operator);3) facilitating fine-grained examination of the correspondence between the line chart and the identified dataset. By seamlessly combining dataset retrieval with visual refinement and validation mechanisms, DDLC offers a comprehensive solution for the data-driven exploration and analysis. © 2024, VLDB Endowment. All rights reserved.

关键词： data aggregation

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Interaction visualization for Analysing and Improving User Models 32

Interaction Visualization for Analysing and Improving User M...

引用

32nd ACM conference on User Modeling, Adaptation and Personalization (ACM UMAP)

作者： Lengauer, Stefan Shao, Lin Tytarenko, Mariia Klaffenboeck, Manfred Schreck, Tobias Graz Univ Technol Graz Austria TU Wien Vienna Austria

ISBN: (纸本)9798400704666

Many web-based systems such as online retail, information systems or search engines track the interactions users have with them. Tracked data can comprise high-level information like dwelling time, reviewed items, and clicked elements, but also fine-grained information in the form of mouse trajectories and keystrokes. While these data are often fed into user- or behavior models in recommender systems, there are few approaches for interactive visual exploration of multi-modal and complex interaction patterns. Yet, the thorough analysis could reveal important insights for the design and evaluation of said models. We propose a suitable visual analysis approach that allows to validate and correct models in an intuitive and interactive manner. Our tool provides insights into concrete user (inter)actions and also estimates more complex behavioral patterns. Level of detail views in our system outlines the certainty of detected behaviors and serve the explainability. Our approach can help engineers to understand user interactions and improve behavioral models.

关键词： User Modelling Model Validation and analysis Interaction visualization

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EmoVIT: Revolutionizing Emotion Insights with visual Instruction Tuning

EmoVIT: Revolutionizing Emotion Insights with Visual Instruc...

引用

IEEE/CVF conference on Computer Vision and Pattern Recognition (CVPR)

作者： Xie, Hongxia Peng, Chu-Jun Tseng, Yu-Wen Chen, Hung-Jen Hsu, Chan-Feng Shuai, Hong-Han Cheng, Wen-Huang Jilin Univ Changchun Peoples R China Natl Taiwan Univ Taipei Taiwan Natl Yang Ming Chiao Tung Univ Hsinchu Taiwan

ISBN: (纸本)9798350353006

visual Instruction Tuning represents a novel learning paradigm involving the fine-tuning of pre-trained language models using task-specific instructions. This paradigm shows promising zero-shot results in various natural language processing tasks but is still unexplored in vision emotion understanding. In this work, we focus on enhancing the model's proficiency in understanding and adhering to instructions related to emotional contexts. Initially, we identify key visual clues critical to visual emotion recognition. Subsequently, we introduce a novel GPT-assisted pipeline for generating emotion visual instruction data, effectively addressing the scarcity of annotated instruction data in this domain. Expanding on the groundwork established by InstructBLIP, our proposed EmoVIT architecture incorporates emotion-specific instruction data, leveraging the powerful capabilities of Large Language Models to enhance performance. Through extensive experiments, our model showcases its proficiency in emotion classification, adeptness in affective reasoning, and competence in comprehending humor. The comparative analysis provides a robust benchmark for Emotion visual Instruction Tuning in the era of LLMs, providing valuable insights and opening avenues for future exploration in this domain. Our code is available at https://***/aimmemotion/EmoVIT.

关键词： Emotion Recognition Large Language Model visual Instruction Tuning

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Applying visual analytics to firearms trafficking trails for the extraction of strategic intelligence

Applying visual analytics to firearms trafficking trails for...

引用

2024 IEEE International conference on Big data, Bigdata 2024

作者： Adamakis, E. Sykianaki, E. Margetis, G. Ntoa, S. Stephanidis, C. Foundation for Research and Technology Hellas Institute of Computer Science Heraklion Greece University of Crete Department of Computer Science Heraklion Greece

ISBN: (纸本)9798350362480

Big data analysis and insight extraction are critical in contemporary large-scale criminal investigations. Analyzing large sets of information related to criminal activities can assist in the identification of correlations between records which can be utilized as strategic intelligence information for the coordination of law enforcement efforts. A Law Enforcement Agency (LEA) officer tasked with this analysis requires tools that can enable Big data exploration while being intuitive and without requiring the need for prior knowledge. A common practice of data analysis software is the ability to create dashboards that can provide all the necessary visualizations and filters to support such an analysis. However, when it comes to dashboard-wide data exploration through drill-down or roll-up analysis;review and evaluation of correlations between data records;and creation of collections with information important to an investigation, current solutions fall short. In this paper, we present a system that addresses these limitations by facilitating the visualization and exploration of diverse data sources, allowing for individual or concurrent analysis via user-configured dashboards. Individual data records of interest to the analysis can be reviewed and their correlations evaluated by the user, allowing for the creation of collections of records and their relationships based on formalized types of correlations. © 2024 IEEE.

关键词： Crime

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Understanding visual Artists' Values and Attitudes towards Collaboration, Technology, and AI 24

Understanding Visual Artists' Values and Attitudes towards C...

引用

50th Graphics Interface conference (GI)

作者： Johnston, Hannah Thue, David Carleton Univ Ottawa ON Canada

ISBN: (纸本)9798400718281

Artificial Intelligence (AI) tools have recently gained widespread interest for image creation, but tool developers have largely focused on technical capabilities or specialized domain uses, rather than visual artists as users. We collected survey data from 89 practising visual artists and conducted follow-up interviews with 30 of them, to better understand their diverse needs and values. Through reflexive thematic analysis, we explored visual artists' attitudes towards collaboration in art creation both with human artists and with AI- and other technology-based support systems. Our results suggest that the focus of popular AI tools on high-quality, finished images does not meet the needs of visual artists. Instead, they wanted reference images, ideation support, and variant exploration. We identified similarities and differences between how visual artists view collaboration with other artists or with machine support, enabling designers of new tools to adopt a more user-centered approach.

关键词： visual Art Collaboration Artificial Intelligence Creativity Support Tools User Experience Generative Research

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Development and Application of data analysis and visualization Software in Oil Testing Process

Development and Application of Data Analysis and Visualizati...

引用

2024 International conference on Telecommunications and Power Electronics, TELEPE 2024

作者： Wu, Liqiang Jiang, Wanxue Chen, Zhi Downhole Services Company Cnpc Bohai Drilling Engineering Company Limited Hebei Renqiu062550 China

ISBN: (纸本)9798350369212

This study is devoted to the development and application of data analysis and visualization software in the process of oil testing, aiming at improving the understanding of underground reservoirs and the accuracy of reservoir development decisions. Through in-depth investigation and analysis of the requirements of geological data analysis and visualization, a powerful Oilanalysis software platform is designed and implemented, which can effectively process and analyze various types of geological data and provide intuitive and interactive visual display. The software developed in this study has flexible data import and processing functions, and can handle various geological data types including logging data, seismic data and core analysis data. At the same time, the software also integrates various data analysis and visualization algorithms, including stratigraphic modeling, porosity analysis, seismic exploration profile display and other functions, providing users with comprehensive data analysis and display tools. Through the analysis of practical application cases, the practical utility of the software in the process of oil testing is verified, which proves that it has important application value and popularization prospect. © 2024 IEEE.

关键词： data accuracy

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The Role of visualization in Genomics data analysis Workflows: The Interviews

The Role of Visualization in Genomics Data Analysis Workflow...

引用

IEEE conference on visualization and visual Analytics (IEEE VIS)

作者： L'Yi, Sehi Wang, Qianwen Gehlenborg, Nils Harvard Med Sch Boston MA 02115 USA

ISBN: (纸本)9798350325577

The diversity of genome-mapped data and analysis tasks makes it challenging for a single visualization tool to fulfill all visualization needs. To design a visualization tool that supports various genomics workflows of users, it is critical to first gain insights into the diverse workflows and the limitations of existing genomics tools for supporting them. In this paper, we conducted semi-structured interviews (N=9) to understand the role of visualization in genomics data analysis workflows. Our main goals were to identify various genomics workflows, from data analysis to visual exploration and presentation, and to observe challenges that genomics analysts encounter in these workflows when using existing tools. Through the interviews, we found several unique characteristics of genomics workflows, such as the use of multiple visualization tools and many repetitive tasks, which can significantly affect the overall performance. Based on our findings, we discuss implications for designing effective visualization authoring tools that tightly support genomics workflows, such as supporting automation and reproducibility.

关键词： H.5.2 [Information Systems]: Information Interfaces and Presentation (e.g. HCI) User Interfaces

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