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Baseball Timeline: Summarizing Baseball Plays Into a Static visualization

COMPUTER GRAPHICS FORUM 2018年第3期37卷 491-501页

作者： Ono, Jorge P. Dietrich, Carlos Silva, Claudio T. NYU New York NY 10003 USA

In sports, Play Diagrams are the standard way to represent and convey information. They are widely used by coaches, managers, journalists and fans in general. There are situations where diagrams may be hard to understand, for example, when several actions are packed in a certain region of the field or there are just too many actions to be transformed in a clear depiction of the play. The representation of how actions develop through time, in particular, may be hardly achieved on such diagrams. The time, and the relationship among the actions of the players through time, is critical on the depiction of complex plays. In this context, we present a study on how player actions may be clearly depicted on 2D diagrams. The study is focused on Baseball plays, a sport where diagrams are heavily used to summarize the actions of the players. We propose a new and simple approach to represent spatiotemporal information in the form of a timeline. We designed our visualization with a requirement driven approach, conducting interviews and fulfilling the needs of baseball experts and expert-fans. We validate our approach by presenting a detailed analysis of baseball plays and conducting interviews with four domain experts.

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

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Visualizing Multidimensional Data with Order Statistics

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COMPUTER GRAPHICS FORUM 2018年第3期37卷 277-287页

作者： Raj, M. Whitaker, R. T. Univ Utah Salt Lake City UT 84112 USA

Multidimensional data sets are common in many domains, and dimensionality reduction methods that determine a lower dimensional embedding are widely used for visualizing such data sets. This paper presents a novel method to project data onto a lower dimensional space by taking into account the order statistics of the individual data points, which are quantified by their depth or centrality in the overall set. Thus, in addition to conveying relative distances in the data, the proposed method also preserves the order statistics, which are often lost or misrepresented by existing visualization methods. The proposed method entails a modification of the optimization objective of conventional multidimensional scaling (MDS) by introducing a term that penalizes discrepancies between centrality structures in the original space and the embedding. We also introduce two strategies for visualizing lower dimensional embeddings of multidimensional data that takes advantage of the coherent representation of centrality provided by the proposed projection method. We demonstrate the effectiveness of our visualization with comparisons on different kinds of multidimensional data, including categorical and multimodal, from a variety of domains such as botany and health care.

关键词： CCS Concepts •human‐centered computing → information visualization Visual analytics •Mathematics of computing → Mathematical optimization

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Towards Easy Comparison of Local Businesses Using Online Reviews

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COMPUTER GRAPHICS FORUM 2018年第3期37卷 63-74页

作者： Wang, Yong Haleem, Hammad Shi, Conglei Wu, Yanhong Zhao, Xun Fu, Siwei Qu, Huamin Hong Kong Univ Sci & Technol Hong Kong Peoples R China Airbnb Inc San Francisco CA USA Vis Res Palo Alto CA USA

With the rapid development of e-commerce, there is an increasing number of online review websites, such as Yelp, to help customers make better purchase decisions. Viewing online reviews, including the rating score and text comments by other customers, and conducting a comparison between different businesses are the key to making an optimal decision. However, due to the massive amount of online reviews, the potential difference of user rating standards, and the significant variance of review time, length, details and quality, it is difficult for customers to achieve a quick and comprehensive comparison. In this paper, we present E-Comp, a carefully-designed visual analytics system based on online reviews, to help customers compare local businesses at different levels of details. More specifically, intuitive glyphs overlaid on maps are designed for quick candidate selection. Grouped Sankey diagram visualizing the rating difference by common customers is chosen for more reliable comparison of two businesses. Augmented word cloud showing adjective-noun word pairs, combined with a temporal view, is proposed to facilitate in-depth comparison of businesses in terms of different time periods, rating scores and features. The effectiveness and usability of E-Comp are demonstrated through a case study and in-depth user interviews.

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

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