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Titlebook: Algorithms for Big Data; DFG Priority Program Hannah Bast,Claudius Korzen,Manuel Penschuck Book‘‘‘‘‘‘‘‘ 2022 The Editor(s) (if applicable)

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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/a/image/153204.jpg
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,Gehörsrüge und Gegenvorstellung,dge from such data in reasonable time. Addressing scalability as well as other requirements such as good usability and a rich feature set, the open-source software . has established itself as a popular tool for large-scale network analysis. This chapter provides a brief overview of the contributions
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,Überblick über das Finanzgericht,atabases of small molecules. Since a direct relationship between the structure of these molecules and their effect (e.g., toxicity) can be assumed in many cases, a wide set of methods is based on the modeling of the molecules as graphs with attributes..Here, we discuss our results concerning . molec
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,Überblick über das Finanzgericht,eoretic problems. This has resulted in an algorithmic toolbox that is by now well-established. However, these theoretical algorithmic ideas have received very little attention from the practical perspective. We survey recent trends in data reduction engineering results for selected problems. Moreove
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,Gehörsrüge und Gegenvorstellung, the previously proposed heuristic Quasi-Threshold Mover (QTM), we present improvements both in terms of running time and quality. We propose a novel, linear-time algorithm that solves the inclusion-minimal variant of this problem, i.e., a set of edge edits such that no subset of them also transform
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