2021 25th International Conference Information Visualisation (IV)最新文献

Enriching Didactic Similarity Measures of Concept Maps by a Deep Learning Based Approach 利用基于深度学习的方法丰富概念图的教学相似性度量

2021 25th International Conference Information Visualisation (IV) Pub Date : 2021-07-01 DOI: 10.1109/IV53921.2021.00049

C. Limongelli, Daniele Schicchi, D. Taibi

{"title":"Enriching Didactic Similarity Measures of Concept Maps by a Deep Learning Based Approach","authors":"C. Limongelli, Daniele Schicchi, D. Taibi","doi":"10.1109/IV53921.2021.00049","DOIUrl":"https://doi.org/10.1109/IV53921.2021.00049","url":null,"abstract":"Concept maps are significant tools able to support several tasks in the educational area such as curriculum design, knowledge organization and modeling, students’ assessment and many others. They are also successfully used in learning activities in which students have to represent domain knowledge according to teacher’s assignment. In this context, the development of Learning Analytics approaches would benefit of methods that automatically compare concept maps. Detecting concept maps similarities is relevant to identify how the same concepts are used in different knowledge representations. Algorithms for comparing graphs have been extensively studied in the literature, but they do not appear appropriate for concept maps. In concept maps, concepts exposed are at least as relevant as the structure that contains them. Neglecting the semantic and didactic aspect inevitably causes inaccuracies and the consequently limited applicability in Learning Analytics approaches. In this work, starting from an algorithm which compares didactic characteristic of concept maps, we present an extension which exploits a semantic approach to catch the actual meaning of the concepts expressed in the nodes of the map.","PeriodicalId":380260,"journal":{"name":"2021 25th International Conference Information Visualisation (IV)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116890233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

[Title page i] [标题页i]

2021 25th International Conference Information Visualisation (IV) Pub Date : 2021-07-01 DOI: 10.1109/iv53921.2021.00001

引用次数: 0

The sight of Justice. Visual knowledge mining, legal data and computational crime analysis 正义的景象。可视化知识挖掘，法律数据和计算犯罪分析

2021 25th International Conference Information Visualisation (IV) Pub Date : 2021-07-01 DOI: 10.1109/IV53921.2021.00050

N. Lettieri, Alfonso Guarino, Delfina Malandrino, R. Zaccagnino

{"title":"The sight of Justice. Visual knowledge mining, legal data and computational crime analysis","authors":"N. Lettieri, Alfonso Guarino, Delfina Malandrino, R. Zaccagnino","doi":"10.1109/IV53921.2021.00050","DOIUrl":"https://doi.org/10.1109/IV53921.2021.00050","url":null,"abstract":"One of the challenges in the emerging field of computational crime analysis is that of extracting actionable knowledge from heterogeneous (both legal and empirical) information hidden into criminal proceedings. Public prosecutors generally deal with information systems that do not provide advanced information extraction functionalities and that boil down to databases containing complaints, criminal records or police reports. In this paper, we dwell on how information visualization can support knowledge mining in criminal investigations by playing a three-fold role: (a) depicting the structural and qualitative features of both criminal organizations and their members; (b) showing the evolution of criminal networks over time; (c) enhance the interaction between the domain expert and computational heuristics in the knowledge construction process. We present three visualizations designed to support knowledge mining in criminal investigations that have been tested with real data and evaluated by legal scholars and public prosecutors within a computational crime analysis project.","PeriodicalId":380260,"journal":{"name":"2021 25th International Conference Information Visualisation (IV)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123552620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

VisuaLeague: Visual Analytics of Multiple Games visualague:多款游戏的视觉分析

2021 25th International Conference Information Visualisation (IV) Pub Date : 2021-07-01 DOI: 10.1109/IV53921.2021.00019

A. Afonso, M. B. Carmo, Rafael Afonso

{"title":"VisuaLeague: Visual Analytics of Multiple Games","authors":"A. Afonso, M. B. Carmo, Rafael Afonso","doi":"10.1109/IV53921.2021.00019","DOIUrl":"https://doi.org/10.1109/IV53921.2021.00019","url":null,"abstract":"One of the most popular eSports (electronic sports) game types practiced is the Multiplayer Online Battle Arena (MOBA) genre, represented by one of the most popular competitive games, League of Legends (LoL). As in many traditional sports, to improve player and team performance, players and coaches analyze all the game events, such as, the positions and trajectories of the players, representing their movements, events and actions they performed during the game (spatial and temporal data). This paper presents VisuaLeague, a visualization tool for analysis of LoL matches for single player, teams, professional matches, and multiple games. The tool offers interaction with the visualizations, filtering and aggregation of data, and clustering to solve the common problems presented in analysis with voluminous amount of data, like cluttering and overlapping. We evaluated VisuaLeague through a user study covering the various types of analysis with two professional coaches. Results indicate that the tool was overall intuitive, useful, efficient and innovative and coaches show a particular interest in the analysis of professional training matches and multiple games as those provide visualizations that often lack in common tools, specially, regarding spatio-temporal data.","PeriodicalId":380260,"journal":{"name":"2021 25th International Conference Information Visualisation (IV)","volume":"649 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122698239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

μ Viz: Visualization of Microservices 微服务的可视化

2021 25th International Conference Information Visualisation (IV) Pub Date : 2021-07-01 DOI: 10.1109/IV53921.2021.00028

S. Silva, Jaime Correia, André Bento, Filipe Araújo, R. Barbosa

{"title":"μ Viz: Visualization of Microservices","authors":"S. Silva, Jaime Correia, André Bento, Filipe Araújo, R. Barbosa","doi":"10.1109/IV53921.2021.00028","DOIUrl":"https://doi.org/10.1109/IV53921.2021.00028","url":null,"abstract":"Microservice architectures have become very popular and widely adopted by the industry, because of the benefits they bring to the software development process and resulting systems, such as parallel development, modularity and scalability. However, as interfaces become more fine-grained and systems grown in size, complexity is moved from the component services to their interactions, eventually leading to intricate workflows that are hard to observe, visualize, and understand. This problem is compounded by the typically high workloads that produce intractable amounts of observation data. To deal with these challenges, operators need support from tools able to take in observation data, in particular tracing, and provide a fast and intuitive understanding of which components or workflows require attention and how are they affecting a module, service, instance, or the whole application. In this paper, we present the design of a microservice visualization application that can fill a gap that exists in leveraging tracing data, aggregating and navigating it in ways that are actionable for operators. Our application provides multiple views of the system and uses spatial and hierarchical navigation using flip zoom to simplify their exploration, while preserving context. Our application can provide a better understanding of the system than existing applications that lack navigability and do not preserve context when switching between different services, layers or views.","PeriodicalId":380260,"journal":{"name":"2021 25th International Conference Information Visualisation (IV)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128673663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A Piloting Study of Measuring Effectiveness of Virtual Reality in Understanding a New Concept in Educational Support Systems 理解教育支持系统新概念中虚拟现实有效性测量的初步研究

2021 25th International Conference Information Visualisation (IV) Pub Date : 2021-07-01 DOI: 10.1109/IV53921.2021.00036

Shingo Taniuchi, Kiyotaka Kawahara, Mariko Sasakura

引用次数: 0

Automated Insights on Visualizations with Natural Language Generation 使用自然语言生成的可视化自动洞察

2021 25th International Conference Information Visualisation (IV) Pub Date : 2021-07-01 DOI: 10.1109/IV53921.2021.00052

R. Brath, Craig Hagerman

引用次数: 1

Organizing and Liaison Program Committee 组织及联络计划委员会

2021 25th International Conference Information Visualisation (IV) Pub Date : 2021-07-01 DOI: 10.1109/iv53921.2021.00008

引用次数: 0

Insights from Neuroscience: Exploring Highly Sensitive Persons’ Use of Knowledge Visualization 来自神经科学的见解:探索高度敏感的人对知识可视化的使用

2021 25th International Conference Information Visualisation (IV) Pub Date : 2021-07-01 DOI: 10.1109/IV53921.2021.00051

Sabrina Bresciani, S. Kernbach

引用次数: 0

PCAPFunnel: A Tool for Rapid Exploration of Packet Capture Files PCAPFunnel:一个快速探索包捕获文件的工具

2021 25th International Conference Information Visualisation (IV) Pub Date : 2021-07-01 DOI: 10.1109/IV53921.2021.00021

Juraj Uhlár, Martin Holkovic, Vít Rusňák

{"title":"PCAPFunnel: A Tool for Rapid Exploration of Packet Capture Files","authors":"Juraj Uhlár, Martin Holkovic, Vít Rusňák","doi":"10.1109/IV53921.2021.00021","DOIUrl":"https://doi.org/10.1109/IV53921.2021.00021","url":null,"abstract":"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.","PeriodicalId":380260,"journal":{"name":"2021 25th International Conference Information Visualisation (IV)","volume":"457 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113996031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4