31,199 research outputs found

    Graph-Drawing Contest Report

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    This report describes the Sixth Annual Graph Drawing Contest, held in conjunction with the 1999 Graph Drawing Symposium in Prague, Czech Republic. The purpose of the contest is to monitor and challenge the current state of the art in graph-drawing technology

    Graph-drawing contest report

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    Graph-Drawing contest report

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    The Open Graph Archive: A Community-Driven Effort

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    In order to evaluate, compare, and tune graph algorithms, experiments on well designed benchmark sets have to be performed. Together with the goal of reproducibility of experimental results, this creates a demand for a public archive to gather and store graph instances. Such an archive would ideally allow annotation of instances or sets of graphs with additional information like graph properties and references to the respective experiments and results. Here we examine the requirements, and introduce a new community project with the aim of producing an easily accessible library of graphs. Through successful community involvement, it is expected that the archive will contain a representative selection of both real-world and generated graph instances, covering significant application areas as well as interesting classes of graphs.Comment: 10 page

    Promotion and Relegation in Sporting Contests

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    The conventional model of a team sports league is based on the North American major leagues which have a fixed number of members, entry is rare and only granted by permission of the incumbents (the closed system). European soccer leagues operate a system of promotion and relegation, effectively permitting entry on merit to all-comers (the open system). This paper examines the impact of openness on the incentive of teams to invest (expend effort) and share resources (redistribution) in the context of a Tullock contest. The main conclusion of the paper is that openness tends to enhance effort incentives, but diminishes the incentive to share income.

    Studying the Emerging Global Brain: Analyzing and Visualizing the Impact of Co-Authorship Teams

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    This paper introduces a suite of approaches and measures to study the impact of co-authorship teams based on the number of publications and their citations on a local and global scale. In particular, we present a novel weighted graph representation that encodes coupled author-paper networks as a weighted co-authorship graph. This weighted graph representation is applied to a dataset that captures the emergence of a new field of science and comprises 614 papers published by 1,036 unique authors between 1974 and 2004. In order to characterize the properties and evolution of this field we first use four different measures of centrality to identify the impact of authors. A global statistical analysis is performed to characterize the distribution of paper production and paper citations and its correlation with the co-authorship team size. The size of co-authorship clusters over time is examined. Finally, a novel local, author-centered measure based on entropy is applied to determine the global evolution of the field and the identification of the contribution of a single author's impact across all of its co-authorship relations. A visualization of the growth of the weighted co-author network and the results obtained from the statistical analysis indicate a drift towards a more cooperative, global collaboration process as the main drive in the production of scientific knowledge.Comment: 13 pages, 9 figure

    Experimental Evaluation of Book Drawing Algorithms

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    A kk-page book drawing of a graph G=(V,E)G=(V,E) consists of a linear ordering of its vertices along a spine and an assignment of each edge to one of the kk pages, which are half-planes bounded by the spine. In a book drawing, two edges cross if and only if they are assigned to the same page and their vertices alternate along the spine. Crossing minimization in a kk-page book drawing is NP-hard, yet book drawings have multiple applications in visualization and beyond. Therefore several heuristic book drawing algorithms exist, but there is no broader comparative study on their relative performance. In this paper, we propose a comprehensive benchmark set of challenging graph classes for book drawing algorithms and provide an extensive experimental study of the performance of existing book drawing algorithms.Comment: Appears in the Proceedings of the 25th International Symposium on Graph Drawing and Network Visualization (GD 2017
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