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Boxer: Interactive Comparison of Classifier Results

COMPUTER GRAPHICS FORUM 2020年第3期39卷 181-193页

作者： Gleicher, Michael Barve, Aditya Yu, Xinyi Heimerl, Florian Univ Wisconsin Madison WI 53706 USA

Machine learning practitioners often compare the results of different classifiers to help select, diagnose and tune models. We present Boxer, a system to enable such comparison. Our system facilitates interactive exploration of the experimental results obtained by applying multiple classifiers to a common set of model inputs. The approach focuses on allowing the user to identify interesting subsets of training and testing instances and comparing performance of the classifiers on these subsets. The system couples standard visual designs with set algebra interactions and comparative elements. This allows the user to compose and coordinate views to specify subsets and assess classifier performance on them. The flexibility of these compositions allow the user to address a wide range of scenarios in developing and assessing classifiers. We demonstrate Boxer in use cases including model selection, tuning, fairness assessment, and data quality diagnosis.

关键词： CCS Concepts • human‐centered computing → visualization Visual analytics Information visualization

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WarehouseVis: A Visual Analytics Approach to Facilitating Warehouse Location Selection for Business Districts

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COMPUTER GRAPHICS FORUM 2020年第3期39卷 483-495页

作者： Li, Q. Liu, Q. Q. Tang, C. F. Li, Z. W. Wei, S. C. Peng, X. R. Zheng, M. H. Chen, T. J. Yang, Q. WeBank AI Grp Shenzhen Guangdong Peoples R China Hong Kong Univ Sci & Technol Dept Comp Sci & Engn Hong Kong Peoples R China

Selecting a proper warehouse location serving to satisfy the demands of the goods from a certain business area is important to a successful retail business. However, the large solution space, uncertain traffic conditions, and varying business preferences impose great challenges on warehouse location selection. Conventional approaches mainly summarize relevant evaluation criteria and compile them into an analysis report to facilitate rapid data absorption but fail to support a comprehensive and joint decision-making process in warehouse location selection. In this paper, we propose a visual analytics approach to facilitating warehouse location selection. We first visually centralize relevant information of warehouses and adapts a widely-used methodology to efficiently rank warehouse candidates. We then design a delivering estimation model based on massive logistics trajectories to resolve the uncertainty issue of traffic conditions of warehouses. Based on these techniques, an interactive framework is proposed to generate and explore the candidate warehouses. We conduct a case study and a within-subject study with baseline systems to assess the efficacy of our system. Experts' feedback also suggests that our approach indeed helps them better tackle the problem of finding an ideal warehouse in the field of retail logistics management.

关键词： CCS Concepts • human‐centered computing → visualization visualization design and evaluation methods

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Multiple Views: different meanings and collocated words

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COMPUTER GRAPHICS FORUM 2019年第3期38卷 79-93页

作者： Roberts, J. C. Al-maneea, H. Butcher, P. W. S. Lew, R. Rees, G. Sharma, N. Frankenberg-Garcia, A. Bangor Univ Bangor Gwynedd Wales Basrah Univ Basrah Iraq Adam Mickiewicz Univ Poznan Poland Univ Surrey Guildford Surrey England

We report on an in-depth corpus linguistic study on multiple views' terminology and word collocation. We take a broad interpretation of these terms, and explore the meaning and diversity of their use in visualisation literature. First we explore senses of the term multiple views' (e.g., multiple views' can mean juxtaposition, many viewport projections or several alternative opinions). Second, we investigate term popularity and frequency of occurrences, investigating usage of multiple' and view' (e.g., multiple views, multiple visualisations, multiple sets). Third, we investigate word collocations and terms that have a similar sense (e.g., multiple views, side-by-side, small multiples). We built and used several corpora, including a 6-million-word corpus of all IEEE Visualisation conference articles published in IEEE Transactions on Visualisation and Computer Graphics 2012 to 2017. We draw on our substantial experience from early work in coordinated and multiple views, and with collocation analysis develop several lists of terms. This research provides insight into term use, a reference for novice and expert authors in visualisation, and contributes a taxonomy of multiple view' terms.

关键词： CCS Concepts • human‐centered computing → visualization visualization theory concepts and paradigms • Applied computing → Arts and humanities Education

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Latent Space Cartography: Visual Analysis of Vector Space Embeddings

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COMPUTER GRAPHICS FORUM 2019年第3期38卷 67-78页

作者： Liu, Yang Jun, Eunice Li, Qisheng Heer, Jeffrey Univ Washington Paul G Allen Sch Comp Sci & Engn Seattle WA 98195 USA

Latent spaces-reduced-dimensionality vector space embeddings of data, fit via machine learning-have been shown to capture interesting semantic properties and support data analysis and synthesis within a domain. Interpretation of latent spaces is challenging because prior knowledge, sometimes subtle and implicit, is essential to the process. We contribute methods for latent space cartography, the process of mapping and comparing meaningful semantic dimensions within latent spaces. We first perform a literature survey of relevant machine learning, natural language processing, and scientific research to distill common tasks and propose a workflow process. Next, we present an integrated visual analysis system for supporting this workflow, enabling users to discover, define, and verify meaningful relationships among data points, encoded within latent space dimensions. Three case studies demonstrate how users of our system can compare latent space variants in image generation, challenge existing findings on cancer transcriptomes, and assess a word embedding benchmark.

关键词： CCS Concepts • human‐centered computing → visualization Visual analytics

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Toward Understanding Representation Methods in visualization Recommendations through Scatterplot Construction Tasks

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COMPUTER GRAPHICS FORUM 2019年第3期38卷 201-211页

作者： L'Yi, Sehi Chang, Youli Shin, DongHwa Seo, Jinwook Seoul Natl Univ Seoul South Korea

Most visualization recommendation systems predominantly rely on graphical previews to describe alternative visual encodings. However, since InfoVis novices are not familiar with visual representations (e.g., interpretation barriers [GTS10]), novices might have difficulty understanding and choosing recommended visual encodings. As an initial step toward understanding effective representation methods for visualization recommendations, we investigate the effectiveness of three representation methods (i.e., previews, animated transitions, and textual descriptions) under scatterplot construction tasks. Our results show how different representations individually and cooperatively help users understand and choose recommended visualizations, for example, by supporting their expect-and-confirm process. Based on our study results, we discuss design implications for visualization recommendation interfaces.

关键词： CCS Concepts • human‐centered computing → visualization User studies

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SEEVis: A Smart Emergency Evacuation Plan visualization System with Data-Driven Shot Designs

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COMPUTER GRAPHICS FORUM 2020年第3期39卷 523-535页

作者： Li, Q. Liu, Y. J. Chen, L. Yang, X. C. Peng, Y. Yuan, X. R. Wijerathne, M. L. L. Tsinghua Univ Sch Software Beijing Peoples R China Beijing Natl Res Ctr Informat Sci & Technol BNRis Beijing Peoples R China WeBank AI Grp Shenzhen Guangdong Peoples R China Peking Univ Beijing Peoples R China Univ Tokyo Tokyo Japan

Despite the significance of tracking human mobility dynamics in a large-scale earthquake evacuation for an effective first response and disaster relief, the general understanding of evacuation behaviors remains limited. Numerous individual movement trajectories, disaster damages of civil engineering, associated heterogeneous data attributes, as well as complex urban environment all obscure disaster evacuation analysis. Although visualization methods have demonstrated promising performance in emergency evacuation analysis, they cannot effectively identify and deliver the major features like speed or density, as well as the resulting evacuation events like congestion or turn-back. In this study, we propose a shot design approach to generate customized and narrative animations to track different evacuation features with different exploration purposes of users. Particularly, an intuitive scene feature graph that identifies the most dominating evacuation events is first constructed based on user-specific regions or their tracking purposes on a certain feature. An optimal camera route, i.e., a storyboard is then calculated based on the previous user-specific regions or features. For different evacuation events along this route, we employ the corresponding shot design to reveal the underlying feature evolution and its correlation with the environment. Several case studies confirm the efficacy of our system. The feedback from experts and users with different backgrounds suggests that our approach indeed helps them better embrace a comprehensive understanding of the earthquake evacuation.

关键词： CCS Concepts • human‐centered computing → visualization visualization design and evaluation methods

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Topic Tomographies (TopTom): a visual approach to distill information from media streams

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COMPUTER GRAPHICS FORUM 2019年第3期38卷 609-621页

作者： Gobbo, B. Balsamo, D. Mauri, M. Bajardi, P. Panisson, A. Ciuccarelli, P. Politecn Milan Milan Italy ISI Fdn Turin Italy Univ Turin Turin Italy

In this paper we present Top Tom, a digital platform whose goal is to provide analytical and visual solutions for the exploration of a dynamic corpus of user-generated messages and media articles, with the aim of i) distilling the information from thousands of documents in a low-dimensional space of explainable topics, ii) cluster them in a hierarchical fashion while allowing to drill down to details and stories as constituents of the topics, iii) spotting trends and anomalies. Top Tom implements a batch processing pipeline able to run both in near-real time with time stamped data from streaming sources and on historical data with a temporal dimension in a cold start mode. The resulting output unfolds along three main axes: time, volume and semantic similarity (i.e. topic hierarchical aggregation). To allow the browsing of data in a multiscale fashion and the identification of anomalous behaviors, three visual metaphors were adopted from biological and medical fields to design visualizations, i.e. the flowing of particles in a coherent stream, tomographic cross sectioning and contrast-like analysis of biological tissues. The platform interface is composed by three main visualizations with coherent and smooth navigation interactions: calendar view, flow view, and temporal cut view. The integration of these three visual models with the multiscale analytic pipeline proposes a novel system for the identification and exploration of topics from unstructured texts. We evaluated the system using a collection of documents about the emerging opioid epidemics in the United States.

关键词： CCS Concepts • human‐centered computing → visualization • Information systems → Document topic models Expert search

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Efficient Optimal Overlap Removal: Algorithms and Experiments

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COMPUTER GRAPHICS FORUM 2019年第3期38卷 713-723页

作者： Meulemans, W. TU Eindhoven Eindhoven Netherlands

Motivated by visualizing spatial data using proportional symbols, we study the following problem: given a set of overlapping squares of varying sizes, minimally displace the squares as to remove the overlap while maintaining the orthogonal order on their centers. Though this problem is NP-hard, we show that rotating the squares by 45 degrees into diamonds allows for a linear or convex quadratic program. It is thus efficiently solvable even for relatively large instances. This positive result and the flexibility offered by constraint programming allow us to study various trade-offs for overlap removal. Specifically, we model and evaluate through computational experiments the relations between displacement, scale and order constraints for static data, and between displacement and temporal coherence for time-varying data. Finally, we also explore the generalization of our methodology to other shapes.

关键词： CCS Concepts • human‐centered computing → visualization

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