Map labeling is a classical problem in cartography and geographic information systems that asks to place labels for area, line, and point features, with the goal to select and place the maximum number of independent (...
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Map labeling is a classical problem in cartography and geographic information systems that asks to place labels for area, line, and point features, with the goal to select and place the maximum number of independent (i.e., overlap-free) labels. A practically interesting case is point labeling with axis-parallel rectangular labels of common size. In a fully dynamic setting, at each timestep, either a new label appears or an existing label disappears. Then, the challenge is to maintain a maximum cardinality subset of pairwise independent labels with sublinear update time. Motivated by this, we study the maximal independent set (MIS) and maximum independent set (Max-IS) problems on fully dynamic (insertion/deletion model) sets of axis-parallel rectangles of two types: (i) uniform height and width and (ii) uniform height and arbitrary width;both settings can be modeled as rectangle intersection graphs. We present the first deterministic algorithm for maintaining an MIS (and thus a 4-approximate Max-IS) of a dynamic set of uniform rectangles with polylogarithmic update time. This breaks the natural barrier of update time (where is the maximum degree in the graph) for vertex updates presented by Assadi et al. (STOC 2018). We continue by investigating Max-IS and provide a series of deterministic dynamic approximation schemes. For uniform rectangles, we first give an algorithm that maintains a 4-approximate Max-IS with update time. In a subsequent algorithm, we establish the trade-off between approximation quality and update time , for . We conclude with an algorithm that maintains a 2-approximate Max-IS for dynamic sets of unit-height and arbitrary-width rectangles with update time, where is the maximum size of an independent set of rectangles stabbed by any horizontal line. We implement our algorithms and report the results of an experimental comparison exploring the trade-off between solution quality and update time for synthetic and real-world map labeling instances. We
Various state-of-the-art automated reasoning (AR) tools are widely used as backend tools in research of knowledge representation and reasoning as well as in industrial applications. In testing and verification, those ...
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Recently, Kirkpatrick et al. [ALT 2019] and Fallat et al. [JMLR 2023] introduced non-clashing teaching and showed it to be the most efficient machine teaching model satisfying the benchmark for collusion-avoidance set...
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Word clouds are a popular text visualization technique that summarize an input text by displaying its most important words in a compact image. The traditional layout methods do not take proximity effects between words...
Word clouds are a popular text visualization technique that summarize an input text by displaying its most important words in a compact image. The traditional layout methods do not take proximity effects between words into account; this has been improved in semantic word clouds, where relative word placement is controlled by edges in a word similarity graph. We introduce MySemCloud, a new human-in-the-loop tool to visualize and edit semantic word clouds. MySemCloud lets users perform computer-assisted local moves of words, which improve or at least retain the semantic quality. To achieve this, we construct a word similarity graph on which a system of forces is applied to generate a compact initial layout with good semantic quality. The force system also allows us to maintain these attributes after each user interaction, as well as preserve the user’s mental map. The tool provides algorithmic support for the editing operations to help the user enhance the semantic quality of the visualization, while adjusting it to their personal preference. We show that MySemCloud provides high user satisfaction as well as permits users to create layouts of higher quality than state-of-the-art semantic word cloud generation tools.
Hive plots are a graph visualization style placing vertices on a set of radial axes emanating from a common center and drawing edges as smooth curves connecting their respective endpoints. In previous work on hive plo...
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We propose an extension to epistemic ATL with perfect recall, past, and distributed knowledge by strategy contexts and demonstrate the strong completeness of a Hilbert-style proof system for its (. .)-free subset. ...
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In this paper we develop streaming algorithms for the diameter problem and the k-center clustering problem in the sliding window model. In this model we are interested in maintaining a solution for the N most recent p...
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ISBN:
(纸本)9783959770132
In this paper we develop streaming algorithms for the diameter problem and the k-center clustering problem in the sliding window model. In this model we are interested in maintaining a solution for the N most recent points of the stream. In the diameter problem we would like to maintain two points whose distance approximates the diameter of the point set in the window. Our algorithm computes a (3 + ϵ)-approximation and uses O(1/ϵ ln α) memory cells, where α is the ratio of the largest and smallest distance and is assumed to be known in advance. We also prove that under reasonable assumptions obtaining a (3 - ϵ)-approximation requires Ω(N1/3) space. For the k-center problem, where the goal is to find k centers that minimize the maximum distance of a point to its nearest center, we obtain a (6 + ϵ)-approximation using O(k/ϵ lnα) memory cells and a (4 + ϵ)-approximation for the special case k = 2. We also prove that any algorithm for the 2-center problem that achieves an approximation ratio of less than 4 requires Ω(N1/3) space.
We consider the #P-complete problem of counting the number of linear extensions of a poset (#LE);a fundamental problem in order theory with applications in a variety of distinct areas. In particular, we study the comp...
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Hive plots are a graph visualization style placing vertices on a set of radial axes emanating from a common center and drawing edges as smooth curves connecting their respective endpoints. In previous work on hive plo...
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Recently, the first rigorous runtime analyses of ACO algorithms appeared, covering variants of the MAX - MIN ant system and their runtime on pseudo-Boolean functions. Interestingly, a variant called 1-ANT is very sens...
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