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SUMMVIS: Interactive visual analysis of Models, data, and Evaluation for Text Summarization 59

SUMMVIS: Interactive Visual Analysis of Models, Data, and Ev...

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Joint conference of 59th Annual Meeting of the Association-for-Computational-Linguistics (ACL) / 11th International Joint conference on Natural Language Processing (IJCNLP) / 6th Workshop on Representation Learning for NLP (RepL4NLP)

作者： Vig, Jesse Kryscinski, Wojciech Goel, Karan Rajani, Nazneen Fatema Salesforce Res Palo Alto CA 94301 USA Stanford Univ Stanford CA 94305 USA

ISBN: (纸本)9781954085565

Novel neural architectures, training strategies, and the availability of large-scale corpora haven been the driving force behind recent progress in abstractive text summarization. However, due to the black-box nature of neural models, uninformative evaluation metrics, and scarce tooling for model and data analysis, the true performance and failure modes of summarization models remain largely unknown. To address this limitation, we introduce SUMMVIS, an open-source tool for visualizing abstractive summaries that enables fine-grained analysis of the models, data, and evaluation metrics associated with text summarization. Through its lexical and semantic visualizations, the tools offers an easy entry point for in-depth model prediction exploration across important dimensions such as factual consistency or abstractiveness.

关键词： Semantics

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GraphFederator: Federated visual analysis for Multi-party Graphs

GraphFederator: Federated Visual Analysis for Multi-party Gr...

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Pacific (formerly Asia-Pacific APVIS) visualization Symposium

作者： Dongming Han Haiyang Zhu Wei Chen Rusheng Pan Yijing Liu Jiehui Zhou Haozhe Feng Tianye Zhang Xumeng Wang Minfeng Zhu Jianrong Tao Changjie Fan Xiaolong Luke Zhang State Key Lab of CAD&CG Zhejiang University China Hithink RoyalFlush Information Network Co. Ltd. China Wuchan Zhongda Digital Technology Co. Ltd. China Ministry of Education Laboratory of Art and Archaeology Image (Zhejiang University) China College of Computer Science Nankai University China Zhejiang University China Fuxi AI Lab Netease China Pennsylvania State University USA

ISBN: (数字)9798350393804

ISBN: (纸本)9798350393811

This paper presents GraphFederator, a novel approach to construct federated representations of multi-party graphs and supports privacy-preserving visual analysis of graphs. Inspired by the concept of federated learning, we reformulate the analysis of multi-party graphs into a decentralization process. The new federation framework consists of a shared module that is responsible for federated modeling and analysis, and a set of local modules that run on respective graph data. Specifically, we propose a Federated Graph Representation Model (FGRM) that is learned from encrypted characteristics of multi-party graphs in local modules. We also design multiple visualization tools for federated visualization, exploration, and analysis of multi-party graphs. Experimental results on two datasets demonstrate the effectiveness of our approach.

关键词： visualization Analytical models Federated learning data visualization data models Encryption

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Literature analysis on the research status of mass entrepreneurship and innovation training projects : Document metrology based on CNKI database 3

Literature analysis on the research status of mass entrepren...

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3rd International conference on Education, Knowledge and Information Management, ICEKIM 2022

作者： Zhou, Liang Zhang, Wen Jing Lanzhou University of Finance and Economics Information Engineering Institute Lanzhou China Lanzhou University of Finance and Economics Financial Institute Lanzhou China

ISBN: (纸本)9781665416665

Taking the literature of CNKI as the data source and using the literature metrological visual analysis function of CNKI, this paper makes a quantitative analysis on the relevant literature in the research field of "College Students' innovation and entrepreneurship training program"from 2011 to 2021 from the aspects of literature quantity and annual distribution, subject analysis, discipline distribution, source journals, and author distribution, Get the research status and development trend of innovation and entrepreneurship training projects. The results show that in recent ten years, Chinese scholars have paid more and more attention to the research of "College Students' innovation and entrepreneurship training program,"and the keywords with high frequency are "innovation and entrepreneurship,""innovation and entrepreneurship education,""practical teaching"and so on;Education and teaching forum, with 4705 papers published as relevant research papers, has the most significant number of papers, followed by education modernization and laboratory research and exploration, with 393 and 333 papers respectively. Huang Suoyi, Jian Guoming, Zhang Liucheng, and the other three authors wrote a lot, but the distribution of authors was scattered. Higher education, medical education, marginal medical disciplines, computer software, and computer applications ranked among the top three in the number of documents issued. © 2022 IEEE.

关键词： Medical education

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NEXAS: A visual Tool for Navigating and Exploring Argumentation Solution Spaces 9

NEXAS: A Visual Tool for Navigating and Exploring Argumentat...

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9th International conference on Computational Models of Argument (COMMA)

作者： Dachselt, Raimund Gaggl, Sarah Alice Kroetzsch, Markus Mendez, Julian Rusovac, Dominik Yang, Mei Tech Univ Dresden Interact Media Lab Dresden Dresden Germany Tech Univ Dresden Log Programming & Argumentat Grp Dresden Germany Tech Univ Dresden Knowledge Based Syst Grp Dresden Germany Tech Univ Dresden Ctr Tactile Internet CeTI Dresden Germany Tech Univ Dresden Cluster Excellence Phys Life PoL Dresden Germany

ISBN: (纸本)9781643683065;9781643683072

Recent developments on solvers for abstract argumentation frameworks (AFs) made them capable to compute extensions for many semantics efficiently. However, for many input instances these solution spaces can become very large and incomprehensible. So far, for the further exploration and investigation of the AF solution space the user needs to use post-processing methods or handcrafted tools. To compare and explore the solution spaces of two selected semantics, we propose an approach that visually supports the user, via a combination of dimensionality reduction of argumentation extensions and a projection of extensions to sets of accepted or rejected arguments. We introduce the novel web-based visualization tool NEXAS that allows for an interactive exploration of the solution space together with a statistical analysis of the acceptance of individual arguments for the selected semantics, as well as provides an interactive correlation matrix for the acceptance of arguments. We validate the tool with a walk-through along three use cases.

关键词： abstract argumentation visualization solution space exploration

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32nd European Safety and Reliability conference, ESREL 2022

32nd European Safety and Reliability Conference, ESREL 2022

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32nd European Safety and Reliability conference, ESREL 2022

ISBN: (纸本)9789811851834

The proceedings contain 438 papers. The special focus in this conference is on Safety and Reliability. The topics include: Towards a Harmonized Framework for Vessel Inspection via Remote Techniques;Probabilistic Risk analysis in the Overhaul of Aero-engines using a combination of Bayesian Networks and Fuzzy Logic aiming at meeting Civil Aviation Agency Regulations and the requirements AS9100 - A Case Study;comparing distributed and integrated Hazard analysis Environments;influence of Cargo Arrangement on Aircraft Mass Center of Gravity;designing reliable, data-driven maintenance for aircraft systems with applications to the aircraft landing gear brakes;introducing the Structured exploration of Complex Adaptations to learn from operations in an Air Navigation Service Provider;application of Monte Carlo simulation to the reliability estimation of an experimental data Communication System;FBG-based optical sensor networks for thermal measurements in aerospace applications;risk analysis of Unmanned Air Vehicle and Beyond visual Line of Sight Flights: How Does Systems Thinking Add to the Specific Operations Risk Assessment Method?;estimation of industrial assets ageing and maintenance efficiency with interval censored data;application of industry standards and management commitment to asset management in a petrochemical company;a general framework proposal for modelling complex production systems considering maintenance and operative factors under uncertain. Case study in Mining Industry;managing Asset and Supply Chain Resilience Using A Digital Risk Twin;Exploring how automated technology and advanced driver-assistance systems (ADAS) are taught in the Norwegian driver-training industry. A qualitative study;reliability of fault-tolerant system architectures for automated driving systems;optimizing Multiple Reinsurance Contracts.

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Performing Energy-Efficient Motions for Wheeled Mobile Robots by Designing an Orientation Controller 4th

Performing Energy-Efficient Motions for Wheeled Mobile Robo...

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4th International conference on Smart Applications and data analysis, SADASC 2022

作者： Fadlo, Said Ait Elmahjoub, Abdelhafid Rabbah, Nabila Ensam Hassan II University Casablanca Morocco

ISBN: (纸本)9783031204890

Wheeled mobile robots are a good candidate for a wide range of missions as exploration, search, rescue, logistics, and leisure. Many of these missions require the robot to perform long-running time and complex tasks. This article describes the design of an energy-efficient orientation controller for wheeled mobile robots. Specifically, this work compares two models and examines how they influence the mode of mobile robot locomotion. Then, the simulation results demonstrate how this approach provides a good trade-off combination of energy efficiency and the requirement of a fast convergence criterion. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Mobile robots

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The 1st International Workshop on Federated Learning with Graph data (FedGraph) 22

The 1st International Workshop on Federated Learning with Gr...

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31st ACM International conference on Information and Knowledge Management (CIKM)

作者： Yang, Carl Li, Xiaoxiao Baracaldo, Nathalie Shah, Neil He, Chaoyang Lyu, Lingjuan Sun, Lichao Avestimehr, Salman Emory Univ Atlanta GA 30322 USA Univ British Columbia Vancouver BC Canada IBM Res San Jose CA USA Snap Res Seattle WA USA FedML Inc Los Angeles CA USA Sony AI Tokyo Japan Lehigh Univ Bethlehem PA 18015 USA Univ Southern Calif Los Angeles CA 90007 USA

ISBN: (纸本)9781450392365

The field of graph data mining, one of the most important AI research areas, has been revolutionized by graph neural networks (GNNs), which benefit from training on real-world graph data with millions to billions of nodes and links. Unfortunately, the training data and process of GNNs involving graphs beyond millions of nodes are extremely costly on a centralized server, if not impossible. Moreover, due to the increasing concerns about data privacy, emerging data from realistic applications are naturally fragmented, forming distributed private graphs of multiple "data silos", among which direct transferring of data is forbidden. The nascent field of federated learning (FL), which aims to enable individual clients to jointly train their models while keeping their local data decentralized and completely private, is a promising paradigm for large-scale distributed and private training of GNNs. FedGraph2022 aims to bring together researchers from different backgrounds with a common interest in how to extend current FL algorithms to operate with graph data models such as GNNs. FL is an extremely hot topic of large commercial interest and has been intensively explored for machine learning with visual and textual data. The exploration from graph mining researchers and industrial practitioners is timely catching up just recently. There are many unexplored challenges and opportunities, which urges the establishment of an organized and open community to collaboratively advance the science behind it. The prospective participants of this workshop will include researchers and practitioners from both graph mining and federated learning communities, whose interests include, but are not limited to: graph analysis and mining, heterogeneous network modeling, complex data mining, large-scale machine learning, distributed systems, optimization, meta-learning, reinforcement learning, privacy, robustness, explainability, fairness, ethics, and trustworthiness.

关键词： graph mining distributed learning data privacy federated learning graph neural networks

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visual analysis Tool for a BLE Technology based Tracking data 23

Visual Analysis Tool for a BLE Technology based Tracking Dat...

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23rd International conference on Enterprise Information Systems (ICEIS)

作者： Schneider, Flavia A. Branco, Adriano Rodrigues, Ariane M. B. Carvalho, Felipe Barbosa, Simone D. J. Endler, Markus Lopes, Helio Pontificia Univ Catolica Rio de Janeiro Dept Comp Rua Marques Sao Vicente 225 Rio de Janeiro Brazil

ISBN: (纸本)9789897585098

Several systems deal with human mobility. Most of them are for outdoor environments and use mobile phones to capture data. However, there is a growing interest of enterprises to consider indoor movement to take employees and client classes into account. Moreover, they usually want to assign semantics to the visited locations. We propose a visual exploration tool for analyzing the dynamics of individual movements in an indoor environment in this work. We present the use of suitable charts and animations to explore these complex data better. Finally, we argue that one could use our solution to monitor social distancing in indoor environments, which is a sensible thing during the current COVID-19 pandemic.

关键词： Internet of Mobile Things data visualization Indoor Positioning data Mining Information Systems

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Developing a Comprehensive Task Framework for Effective Workforce analysis 25

Developing a Comprehensive Task Framework for Effective Work...

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Companion Proceedings of the ACM on Web conference 2025

作者： Rebecca Dew Mingzhao Li Weidong Liu Sandya Baratha Raj Pearson Melbourne Australia Pearson Sydney Australia

ISBN: (纸本)9798400713316

Effective workforce analysis, planning, and management require a deep understanding of the tasks and skills associated with different roles. This paper introduces a novel methodology for developing a comprehensive task framework that leverages Large Language Models (LLMs) and large-scale job ads data. We first propose an innovative approach to task taxonomy design, which involves the decomposition and reconstruction of tasks into a hierarchical structure based on action-object pairings, systematically refined using LLMs. The methodology extends to integrating the taxonomy with occupation and skill linkages derived from job ads, ensuring alignment with real-world workforce dynamics. Finally, we demonstrate the practical value of this framework through a visual analytics system that enables interactive exploration and analysis of tasks, occupations, and associated skills, highlighting its potential to transform workforce analysis. Demo video: https://***/41txBZK

关键词： gpt

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Research on Interior Design Applications Incorporating Artificial Intelligence Technology

Research on Interior Design Applications Incorporating Artif...

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Intelligent Design (ICID), International conference on

作者： Ning Xian Yazhen Liu College of Design and Art Shenyang Jianzhu University Hunnan Shenyang China

ISBN: (数字)9798331541491

ISBN: (纸本)9798331541507

The purpose of this paper is to discuss the application of interior design incorporating artificial intelligence technology. The rapid development of artificial intelligence technology in the new era has produced innovative contributions to various industries, and interior design is no exception. This paper describes the concepts and development status of artificial intelligence and interior design, and analyzes the advantages and scope of its application in interior design according to the artificial intelligence technology that can be used in interior design. Indepth exploration of the potential of AI technology in the field of interior design, with the help of machine learning, big data analysis, virtual reality, augmented reality and intelligent customer feedback system and other tools, significantly improve the efficiency and quality of the design process, strengthen the interactivity and visual impact of the design.

关键词： Industries Computer science Technological innovation visualization Design methodology Catalysts Collaboration Machine learning Big data Augmented reality

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