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

共 2452 条记录，以下是21-30 订阅

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LFENav: LLM-Based Frontiers exploration for visual Semantic Navigation 20th

LFENav: LLM-Based Frontiers Exploration for Visual Semantic ...

引用

20th International conference on Artificial Intelligence Applications and Innovations (AIAI)

作者： Shi, Yuhong Liu, Jianyi Zheng, Xinhu Natl Key Lab Human Machine Hybrid Augmented Intel Xian 710049 Shaanxi Peoples R China Natl Engn Res Ctr Visual Informat & Applicat Xian 710049 Shaanxi Peoples R China Xi An Jiao Tong Univ Inst Artificial Intelligence & Robot Xian 710049 Shaanxi Peoples R China Hong Kong Univ Sci & Technol Guangzhou Intelligent Transportat Thrust Guangzhou Peoples R China

ISBN: (纸本)9783031632259;9783031632235;9783031632228

Robot navigation in an unknown environment is a challenge task, due to the lack of spatial awareness and semantic understanding of the environment. Previous works mostly rely on learning-based approaches, which need large amount of training data and lack of generalization ability. The emergence of Large Language Models (LLMs) provides a new way for semantic understanding. This paper proposes a method of LLM-based Frontiers exploration for visual semantic Navigation (LFENav), which leverages the rich semantic prior knowledge of LLMs to find next subgoals with the input natural language instruction. Firstly, the semantic map is incrementally constructed and the frontiers are redefine from the observed RGB-D images. A prompt mechanism is designed to embody the Chain-of-Thought (CoT) merit of LLMs. We use geometric costs to compensate the information gap of LLMs in understanding the spatial layout of scenes. Based above, a novel exploration policy is designed by integrating LLM scores and geometric costs to select better frontiers worthy of exploring. Experiments on Habitat-Matterport 3D dataset shows that the success rate of this method is up to 0.638, which is the best performance compared with the existing methods.

关键词： visual sematic navigation frontier exploration large language models

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TivEx: Optimized Processing for Time Series visual exploration 20

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

引用

20th ACS/IEEE International conference on Computer Systems and Applications (AICCSA)

作者： Helal, Heba Sharaf, Mohamed A. Masud, Mohammad M. Chrysanthis, Panos K. United Arab Emirates Univ Coll Informat Technol Al Ain U Arab Emirates Univ Pittsburgh Sch Comp & Informat Pittsburgh PA USA Mansoura Univ Dept Comp Engn & Syst Coll Engn Mansoura Egypt

ISBN: (纸本)9798350319439

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.

关键词： visualization Recommendation Time series data Optimization

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Enabling Activity Based Intelligence with visual Analytics

Enabling Activity Based Intelligence with Visual Analytics

引用

International conference on Military Communications and Information Systems (ICMCIS)

作者： Lavigne, Valerie Bergeron-Guyard, Alexandre Def Res & Dev Canada Valcartier Res Ctr Quebec City PQ Canada

ISBN: (纸本)9798350343854

ThornViz is a visual analytics tool presenting data along multiple perspectives for discovering the unexpected and performing Activity Based Intelligence (ABI) analysis. It leverages a flexible data model along with a graph database to support ABI principles through interactive visual exploration of intelligence data including dynamic filtering and social network analysis techniques. ThornViz was applied to explore adversarial communication network data, to investigate crypto-currency transactions for suspicious financial activity, as well as to look for potential collaborations between NATO scientific activities, which demonstrated its multi-domain support. This paper was originally presented at the NATO Science and Technology Organization Symposium (ICMCIS) organized by the Information Systems Technology (IST) Panel, IST-200 RSY - the ICMCIS, held in Skopje, North Macedonia, 16-17 May 2023

关键词： visual analytics activity based intelligence social network analysis temporal analysis geospatial analysis Sankey diagram

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General Line Coordinates in 3D 27

General Line Coordinates in 3D

引用

27th International conference on Information visualisation (iv) / 19th International conference Computer Graphics, Imaging and visualization (CGiv)

作者： Martinez, Joshua Kovalerchuk, Boris Cent Washington Univ Dept Comp Sci Ellensburg WA 98926 USA

ISBN: (纸本)9798350341614

Interpretable interactive visual pattern discovery in lossless 3D visualization is a promising way to advance machine learning. It enables end users who are not data scientists to take control of the model development process as a self-service. It is conducted in 3D General Line Coordinates (GLC) visualization space, which preserves all n-D information in 3D. This paper presents a system which combines three types of GLC: Shifted Paired Coordinates (SPC), Shifted Tripled Coordinates (STC), and General Line Coordinates-Linear (GLC-L) for interactive visual pattern discovery. A transition from 2-D visualization to 3-D visualization allows for a more distinct visual pattern than in 2-D and it also allows for finding the best data viewing positions, which are not available in 2-D. It enables in-depth visual analysis of various class-specific data subsets comprehensible for end users in the original interpretable attributes. Controlling model overgeneralization by end users is an additional benefit of this approach.

关键词： Interpretable machine learning lossless visualization high-dimensional data general line coordinates. shifted paired coordinates 3D information visualization

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An Explainable Artificial Intelligence Solution for the Practical Application of Employee Turnover 28

An Explainable Artificial Intelligence Solution for the Prac...

引用

28th International conference on Information visualisation (iv)

作者： Leung, Carson K. Imran, Rayan Pazdor, Adam G. M. Souza, Joglas Univ Manitoba Dept Comp Sci Winnipeg MB Canada

ISBN: (纸本)9798350380170;9798350380163

Employee turnover is a significant concern across industries, resulting in wasted training resources and the costs associated with hiring replacements. Understanding the underlying reasons behind employee attrition is crucial for businesses seeking to address this issue. Employing data analytics solutions can lead to substantial savings in terms of training hours and financial resources. However, in addition to accurate predictions of employee turnover, the explainability of these analytics results is equally important to gain user trust. Many existing data analytics techniques provide predictions and recommendations in an opaque "black box" manner, making it challenging for humans to understand the reasoning behind them. In this paper, we present an explainable artificial intelligence (XAI) solution that combines cutting-edge techniques and enhances them to generate practical and comprehensible explanations for endusers. To assess the effectiveness of our XAI solution, we conduct a case study using real-life employee turnover data. The results demonstrate the practicality and usefulness of our XAI solution in applications such as analyzing employee turnover.

关键词： information visualization artificial intelligence (AI) visual knowledge discovery employee analytics employee churn churn analysis workplace analysis explainable artificial intelligence (XAI) trustworthy AI interpretability explainability predictive analytics

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visualization Techniques for the Design and analysis of Dynamic Programming Algorithms 28

Visualization Techniques for the Design and Analysis of Dyna...

引用

28th International conference on Information visualisation (iv)

作者： Zhu, Ying Georgia State Univ Creat Media Ind Inst Atlanta GA 30303 USA

ISBN: (纸本)9798350380170;9798350380163

Dynamic programming is one of the most challenging algorithm design techniques for computer programmers. Students frequently struggle with dynamic programming algorithms in data Structures and Algorithms courses, and software developers often find it difficult to solve dynamic programming problems during job interviews. To address this issue, we have developed a new visualization technique to help students better understand, analyze, and design dynamic programming algorithms. Previous dynamic programming visualizations have primarily focused on illustrating the execution sequence of programs. Our visualizations are designed to help students recognize the common logical patterns shared by a diverse set of problems. Additionally, students can use these visualizations as visual aids to assist them in designing dynamic programming algorithms.

关键词： Algorithm visualization dynamic programming computer science education

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Giving Shape to Words: visual Knowledge Discovery for Textual Contents in Legal Scenarios 27

Giving Shape to Words: Visual Knowledge Discovery for Textua...

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27th International conference on Information visualisation (iv) / 19th International conference Computer Graphics, Imaging and visualization (CGiv)

作者： Lettieri, Nicola Guarino, Alfonso Malandrino, Delfina Zaccagnino, Rocco Del Piano, Salvatore Natl Inst Publ Policy Anal I-00198 Rome Italy Univ Sannio Dept Law Econ Management & Quantitat Methods I-82100 Benevento BN Italy Univ Salerno Comp Sci Dept I-84084 Fisciano SA Italy

ISBN: (纸本)9798350341614

visual Knowledge Discovery (VKD), the emerging research field exploring the integration between Artificial Intelligence and visual Analytics is impacting a growing number of contexts. This paper dwells on the potential intersections between the VKD perspective and the legal world, a scenario for many reasons drawn by the idea of combining empirical insights offered by computation with intuitive, visually-enhanced forms of data mining. We will focus on criminal justice, taking the cue from an ongoing experimental research project that investigates novel applications of computational social science methods - complex network analysis - to analyze criminal organizations for both scientific and investigative purposes. The work will describe the VKD solutions devised to allow public prosecutors to visually browse the content of phone calls and environmental tapping gathered during preliminary inquiries. We will discuss how given visualizations - graph-based visualizations in the first place - can enhance text mining techniques helping to capture in-a-glance communication flows, discussions' topics and both structural and functional features of criminal networks at hand.

关键词： visualization Text mining Crime analysis Legal data visual Knowledge Discovery

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Interactive Parallel Coordinates visualization Platform for Survey data 5

Interactive Parallel Coordinates Visualization Platform for ...

引用

5th International conference on Artificial Intelligence and data Sciences, AiDAS 2024

作者： Bakri, M. Afrina, N.A. Hamiz, M. UiTM Cawangan Melaka Kampus Jasin Melaka Malaysia

ISBN: (纸本)9798331528553

Survey data often encompasses many variables, making it challenging to identify complex relationships. Parallel coordinates visualization offers a powerful solution for exploring these relationships. We propose a web-based application that leverages parallel coordinates to enhance survey data analysis. This user-friendly tool overcomes limitations of traditional methods by enabling interactive exploration of high-dimensional data. The application adheres to the waterfall model for development, ensuring thorough testing and achieving a high System Usability Scale (SUS) score of 86.8%. By providing deeper insights through visual exploration, this application empowers researchers to make more informed decisions. However, well-structured and pre-processed data remains essential for accurate visualizations. Overall, our web-based application with parallel coordinates visualization offers an innovative and efficient approach to survey data analysis. © 2024 IEEE.

关键词： data accuracy

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Creative Insights into Motion: Enhancing Human Activity Understanding with 3D data visualization and Annotation 16

Creative Insights into Motion: Enhancing Human Activity Unde...

引用

16th ACM conference on Creativity and Cognition (C and C)

作者： Browen, Isaac Camarillo-Abad, Hector M. Cibrian, Franceli L. Di Qi, Trudi Chapman Univ Fowler Sch Engn Orange CA 92866 USA Chapman Univ Schmid Coll Sci & Technol Orange CA USA

ISBN: (纸本)9798400704857

This paper presents a novel 3D system for human motion analysis - Motion data visualization and Annotation (MoViAn). Designed to provide a comprehensive visual representation of 3D human motion data, MoViAn incorporates detailed visualization of gaze direction, hand movements, and object interactions, alongside an interactive interface for efficient data annotation. A user study involving eight participants indicates that MoViAn enables users to thoroughly explore and annotate human motion data, with System Usability Scale (SUS) results demonstrating a satisfactory usability level. The contribution of this paper lies in the development of an interactive and usable data analytics tool aimed at deepening the understanding of human behaviors and intentions in various creative, cognitive, and physical activities that ultimately can facilitate the design and creation of innovative tools that enhance human life in multiple domains.

关键词： Human motion analysis 3D visualization data exploration data annotation User interface Usability evaluation

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A Real-Time Sentiment Feedback System: Binary Categorization and Context Understanding Based on Product Reviews 16th

A Real-Time Sentiment Feedback System: Binary Categorization...

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16th International conference on Social Networks analysis and Mining

作者： Buttar, Arshpreet S. Fan, Jiawei Fatoki, Olukoye O. Geleta, Roba Leung, Carson K. Univ Manitoba Winnipeg MB Canada

ISBN: (纸本)9783031785535;9783031785542

In the digital age, user reviews are crucial for decision-making and product development. With the growing volume of Amazon product reviews, traditional analysis methods fall short, highlighting the need for smarter, quicker, and more scalable solutions. In this paper, we present a sentiment analysis system tailored for Amazon reviews, utilizing n-grams for better context comprehension and enabling exploration of the machine learning model via real-time application. Evaluation results show model accuracy by concentrating on positive and negative reviews and fine-tuning hyperparameters.

关键词： social network analysis social network mining big data analytics sentiment analysis Amazon reviews n-grams context understanding machine learning hyperparameter optimization text preprocessing dataset balance

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