Information Visualization最新文献_第7页

VisRuler: Visual analytics for extracting decision rules from bagged and boosted decision trees VisRuler：用于从袋装和增强决策树中提取决策规则的可视化分析

IF 2.3 4区计算机科学

Information Visualization Pub Date : 2021-12-01 DOI: 10.1177/14738716221142005

Angelos Chatzimparmpas, R. M. Martins, A. Kerren

{"title":"VisRuler: Visual analytics for extracting decision rules from bagged and boosted decision trees","authors":"Angelos Chatzimparmpas, R. M. Martins, A. Kerren","doi":"10.1177/14738716221142005","DOIUrl":"https://doi.org/10.1177/14738716221142005","url":null,"abstract":"Bagging and boosting are two popular ensemble methods in machine learning (ML) that produce many individual decision trees. Due to the inherent ensemble characteristic of these methods, they typically outperform single decision trees or other ML models in predictive performance. However, numerous decision paths are generated for each decision tree, increasing the overall complexity of the model and hindering its use in domains that require trustworthy and explainable decisions, such as finance, social care, and health care. Thus, the interpretability of bagging and boosting algorithms—such as random forest and adaptive boosting—reduces as the number of decisions rises. In this paper, we propose a visual analytics tool that aims to assist users in extracting decisions from such ML models via a thorough visual inspection workflow that includes selecting a set of robust and diverse models (originating from different ensemble learning algorithms), choosing important features according to their global contribution, and deciding which decisions are essential for global explanation (or locally, for specific cases). The outcome is a final decision based on the class agreement of several models and the explored manual decisions exported by users. We evaluated the applicability and effectiveness of VisRuler via a use case, a usage scenario, and a user study. The evaluation revealed that most users managed to successfully use our system to explore decision rules visually, performing the proposed tasks and answering the given questions in a satisfying way.","PeriodicalId":50360,"journal":{"name":"Information Visualization","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46943349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Community Fabric: Visualizing communities and structure in dynamic networks 社区结构:动态网络中可视化社区和结构

IF 2.3 4区计算机科学

Information Visualization Pub Date : 2021-10-29 DOI: 10.1177/14738716211056036

Evan Ezell, Seung-Hwan Lim, D. Anderson, R. Stewart

引用次数: 0

Topology-aware space distortion for structured visualization spaces 结构化可视化空间的拓扑感知空间畸变

IF 2.3 4区计算机科学

Information Visualization Pub Date : 2021-10-25 DOI: 10.1177/14738716211053579

Weihang Wang, Sriram Karthik Badam, N. Elmqvist

引用次数: 1

PeaGlyph: Glyph design for investigation of balanced data structures PeaGlyph：用于研究平衡数据结构的Glyph设计

IF 2.3 4区计算机科学

Information Visualization Pub Date : 2021-10-10 DOI: 10.1177/14738716211050602

Kenan Koc, A. McGough, Sara Johansson Fernstad

{"title":"PeaGlyph: Glyph design for investigation of balanced data structures","authors":"Kenan Koc, A. McGough, Sara Johansson Fernstad","doi":"10.1177/14738716211050602","DOIUrl":"https://doi.org/10.1177/14738716211050602","url":null,"abstract":"For many data analysis tasks, such as the formation of well-balanced groups for a fair race or collaboration in learning settings, the balancing between data attributes is at least as important as the actual values of items. At the same time, comparison of values is implicitly desired for these tasks. Even with statistical methods available to measure the level of balance, human judgment, and domain expertise plays an important role in judging the level of balance, and whether the level of unbalance is acceptable or not. Accordingly, there is a need for techniques that improve decision-making in the context of group formation that can be used as a visual complement to statistical analysis. This paper introduces a novel glyph-based visualization, PeaGlyph, which aims to support the understanding of balanced and unbalanced data structures, for instance by using a frequency format through countable marks and salient shape characteristics. The glyph was designed particularly for tasks of relevance for investigation of properties of balanced and unbalanced groups, such as looking-up and comparing values. Glyph-based visualization methods provide flexible and useful abstractions for exploring and analyzing multivariate data sets. The PeaGlyph design was based on an initial study that compared four glyph visualization methods in a joint study, including two base glyphs and their variations. The performance of the novel PeaGlyph was then compared to the best “performers” of the first study through evaluation. The initial results from the study are encouraging, and the proposed design may be a good alternative to the traditional glyphs for depicting multivariate data and allowing viewers to form an intuitive impression as to how balanced or unbalanced a set of objects are. Furthermore, a set of design considerations is discussed in context of the design of the glyphs.","PeriodicalId":50360,"journal":{"name":"Information Visualization","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41489071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

MING: An interpretative support method for visual exploration of multidimensional data MING:一种用于多维数据可视化探索的解释性支持方法

IF 2.3 4区计算机科学

Information Visualization Pub Date : 2021-10-01 DOI: 10.1177/14738716221079589

Benoît Colange, L. Vuillon, S. Lespinats, D. Dutykh

{"title":"MING: An interpretative support method for visual exploration of multidimensional data","authors":"Benoît Colange, L. Vuillon, S. Lespinats, D. Dutykh","doi":"10.1177/14738716221079589","DOIUrl":"https://doi.org/10.1177/14738716221079589","url":null,"abstract":"Dimensionality reduction enables analysts to perform visual exploration of multidimensional data with a low-dimensional map retaining as much as possible of the original data structure. The interpretation of such a map relies on the hypothesis of preservation of neighborhood relations. Namely, distances in the map are assumed to reflect faithfully dissimilarities in the data space, as measured with a domain-related metric. Yet, in most cases, this hypothesis is undermined by distortions of those relations by the mapping process, which need to be accounted for during map interpretation. In this paper, we describe an interpretative support method called Map Interpretation using Neighborhood Graphs (MING) displaying individual neighborhood relations on the map, as edges of nearest neighbors graphs. The level of distortion of those relations is shown through coloring of the edges. This allows analysts to assess the reliability of similarity relations inferred from the map, while hinting at the original structure of data by showing the missing relations. Moreover, MING provides a local interpretation for classical map quality indicators, since the quantitative measure of distortions is based on those indicators. Overall, the proposed method alleviates the mapping-induced bias in interpretation while constantly reminding users that the map is not the data.","PeriodicalId":50360,"journal":{"name":"Information Visualization","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65676457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Improved interactive color visualization approach for hyperspectral images 改进的高光谱图像交互式颜色可视化方法

IF 2.3 4区计算机科学

Information Visualization Pub Date : 2021-09-24 DOI: 10.1177/14738716211048142

Haijun Yu, Shengyang Li

{"title":"Improved interactive color visualization approach for hyperspectral images","authors":"Haijun Yu, Shengyang Li","doi":"10.1177/14738716211048142","DOIUrl":"https://doi.org/10.1177/14738716211048142","url":null,"abstract":"Hyperspectral images (HSIs) have become increasingly prominent as they can maintain the subtle spectral differences of the imaged objects. Designing approaches and tools for analyzing HSIs presents a unique set of challenges due to their high-dimensional characteristics. An improved color visualization approach is proposed in this article to achieve communication between users and HSIs in the field of remote sensing. Under the real-time interactive control and color visualization, this approach can help users intuitively obtain the rich information hidden in original HSIs. Using the dimensionality reduction (DR) method based on band selection, high-dimensional HSIs are reduced to low-dimensional images. Through drop-down boxes, users can freely specify images that participate in the combination of RGB channels of the output image. Users can then interactively and independently set the fusion coefficient of each image within an interface based on concentric circles. At the same time, the output image will be calculated and visualized in real time, and the information it reflects will also be different. In this approach, channel combination and fusion coefficient setting are two independent processes, which allows users to interact more flexibly according to their needs. Furthermore, this approach is also applicable for interactive visualization of other types of multi-layer data.","PeriodicalId":50360,"journal":{"name":"Information Visualization","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45906583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Exploring, browsing and interacting with multi-level and multi-scale dynamics of knowledge 探索、浏览和互动多层次、多尺度的动态知识

IF 2.3 4区计算机科学

Information Visualization Pub Date : 2021-09-23 DOI: 10.1177/14738716211044829

Quentin Lobbé, Alexandre Delanoë, David Chavalarias

{"title":"Exploring, browsing and interacting with multi-level and multi-scale dynamics of knowledge","authors":"Quentin Lobbé, Alexandre Delanoë, David Chavalarias","doi":"10.1177/14738716211044829","DOIUrl":"https://doi.org/10.1177/14738716211044829","url":null,"abstract":"The ICT revolution has given birth to a world of digital traces. A wide number of knowledge-driven domains like science are daily fueled by unlimited flows of textual contents. In order to navigate across these growing constellations of words, interdisciplinary innovations are emerging at the crossroad between social and computational sciences. In particular, complex systems approaches make it now possible to reconstruct multi-level and multi-scale dynamics of knowledge by means of inheritance networks of elements of knowledge called phylomemies. In this article, we will introduce an endogenous way to visualize the multi-level and multi-scale properties of phylomemies. The resulting system will enrich a state-of-the-art tree like representation with the possibility to browse through the evolution of a corpus of documents at different level of observation, to interact with various scales of description, to reconstruct a hierarchical clustering of elements of knowledge and to navigate across complex semantic lineages. We will then formalize a generic macro-to-micro methodology of exploration and implement our system as a free software called the Memiescape. Our system will be illustrated by three use cases that will respectively reconstruct the scientific landscape of the top cited publications of the French CNRS, the evolution of the state of the art of knowledge dynamics visualization and the ongoing discovery process of Covid-19 vaccines.","PeriodicalId":50360,"journal":{"name":"Information Visualization","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41542024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

HyperStorylines: Interactively untangling dynamic hypergraphs HyperStorylines:交互式地解开动态超图

IF 2.3 4区计算机科学

Information Visualization Pub Date : 2021-09-18 DOI: 10.1177/14738716211045007

Vanessa Peña-Araya, Tong Xue, Emmanuel Pietriga, L. Amsaleg, A. Bezerianos

引用次数: 9

Optimal layout of stacked graph for visualizing multidimensional financial time series data 多维金融时间序列数据可视化的堆叠图优化布局

IF 2.3 4区计算机科学

Information Visualization Pub Date : 2021-09-14 DOI: 10.1177/14738716211045005

Yutian He, Hongjun Li

引用次数: 2

STFT-LDA: An algorithm to facilitate the visual analysis of building seismic responses STFT-LDA:一种便于建筑物地震反应可视化分析的算法

IF 2.3 4区计算机科学

Information Visualization Pub Date : 2021-08-21 DOI: 10.1177/14738716211038618

Zhenge Zhao, Danilo Motta, M. Berger, J. Levine, I. B. Kuzucu, R. Fleischman, Afonso Paiva, C. Scheidegger

{"title":"STFT-LDA: An algorithm to facilitate the visual analysis of building seismic responses","authors":"Zhenge Zhao, Danilo Motta, M. Berger, J. Levine, I. B. Kuzucu, R. Fleischman, Afonso Paiva, C. Scheidegger","doi":"10.1177/14738716211038618","DOIUrl":"https://doi.org/10.1177/14738716211038618","url":null,"abstract":"Civil engineers use numerical simulations of a building’s responses to seismic forces to understand the nature of building failures, the limitations of building codes, and how to determine the latter to prevent the former. Such simulations generate large ensembles of multivariate, multiattribute time series. Comprehensive understanding of this data requires techniques that support the multivariate nature of the time series and can compare behaviors that are both periodic and non-periodic across multiple time scales and multiple time series themselves. In this paper, we present a novel technique to extract such patterns from time series generated from simulations of seismic responses. The core of our approach is the use of topic modeling, where topics correspond to interpretable and discriminative features of the earthquakes. We transform the raw time series data into a time series of topics, and use this visual summary to compare temporal patterns in earthquakes, query earthquakes via the topics across arbitrary time scales, and enable details on demand by linking the topic visualization with the original earthquake data. We show, through a surrogate task and an expert study, that this technique allows analysts to more easily identify recurring patterns in such time series. By integrating this technique in a prototype system, we show how it enables novel forms of visual interaction.","PeriodicalId":50360,"journal":{"name":"Information Visualization","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45631431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1