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A Combinatorial Framework for Map Labeling
, 1998
"... The general map labeling problem consists in labeling a set of sites (points, lines, regions) given a set of candidates (rectangles, circles, ellipses, irregularly shaped labels) for each site. A map can be a classical cartographical map, a diagram, a graph or any other figure that needs to be labe ..."
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Cited by 18 (2 self)
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The general map labeling problem consists in labeling a set of sites (points, lines, regions) given a set of candidates (rectangles, circles, ellipses, irregularly shaped labels) for each site. A map can be a classical cartographical map, a diagram, a graph or any other figure that needs
TrajectoryBased Dynamic Map Labeling
 In Proc. 24th Ann. Internat. Symp. Alg. and Comput. (ISAAC’13), volume 8283 of Lecture Notes Comput. Sci
"... Abstract. In this paper we introduce trajectorybased labeling, a new variant of dynamic map labeling, where a movement trajectory for the map viewport is given. We define a general labeling model and study the active range maximization problem in this model. The problem isNPcomplete andW[1]hard. ..."
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Cited by 2 (1 self)
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Abstract. In this paper we introduce trajectorybased labeling, a new variant of dynamic map labeling, where a movement trajectory for the map viewport is given. We define a general labeling model and study the active range maximization problem in this model. The problem isNPcomplete andW[1]hard
gSpan: GraphBased Substructure Pattern Mining
, 2002
"... We investigate new approaches for frequent graphbased pattern mining in graph datasets and propose a novel algorithm called gSpan (graphbased Substructure pattern mining) , which discovers frequent substructures without candidate generation. gSpan builds a new lexicographic order among graphs, and ..."
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Cited by 649 (34 self)
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, and maps each graph to a unique minimum DFS code as its canonical label. Based on this lexicographic order, gSpan adopts the depthfirst search strategy to mine frequent connected subgraphs efficiently. Our performance study shows that gSpan substantially outperforms previous algorithms, sometimes
Efficient semantic matching
, 2004
"... We think of Match as an operator which takes two graphlike structures and produces a mapping between semantically related nodes. We concentrate on classifications with tree structures. In semantic matching, correspondences are discovered by translating the natural language labels of nodes into prop ..."
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Cited by 854 (68 self)
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We think of Match as an operator which takes two graphlike structures and produces a mapping between semantically related nodes. We concentrate on classifications with tree structures. In semantic matching, correspondences are discovered by translating the natural language labels of nodes
Markov Random Field Models in Computer Vision
, 1994
"... . A variety of computer vision problems can be optimally posed as Bayesian labeling in which the solution of a problem is defined as the maximum a posteriori (MAP) probability estimate of the true labeling. The posterior probability is usually derived from a prior model and a likelihood model. The l ..."
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Cited by 517 (18 self)
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. A variety of computer vision problems can be optimally posed as Bayesian labeling in which the solution of a problem is defined as the maximum a posteriori (MAP) probability estimate of the true labeling. The posterior probability is usually derived from a prior model and a likelihood model
AFNI: software for analysis and visualization of functional magnetic resonance neuroimages
 Computers and Biomedical Research
, 1996
"... email rwcoxmcwedu A package of computer programs for analysis and visualization of threedimensional human brain functional magnetic resonance imaging FMRI results is described The software can color overlay neural activation maps onto higher resolution anatomical scans Slices in each cardinal pl ..."
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Cited by 803 (3 self)
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email rwcoxmcwedu A package of computer programs for analysis and visualization of threedimensional human brain functional magnetic resonance imaging FMRI results is described The software can color overlay neural activation maps onto higher resolution anatomical scans Slices in each cardinal
PRACTICAL EXPERIENCE WITH A MAP LABEL PLACEMENT PROGRAM
"... Mathematical optimization algorithms have previously been shown to provide a solution to some map label placement problems. This article discusses computational and carto graphic difficulties encountered and solved while imple menting such techniques in commercial map label placement software. The s ..."
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Mathematical optimization algorithms have previously been shown to provide a solution to some map label placement problems. This article discusses computational and carto graphic difficulties encountered and solved while imple menting such techniques in commercial map label placement software
An ObjectOriented Framework for mapping labels
"... This paper discusses the label bureau based label distribution. ..."
Optimizing active ranges for consistent dynamic map labeling
 IN PROCEEDINGS OF THE 24TH ANNUAL SYMPOSIUM ON COMPUTATIONAL GEOMETRY
, 2008
"... Map labeling encounters unique issues in the context of dynamic maps with continuous zooming and panning—an application with increasing practical importance. In consistent dynamic map labeling, distracting behavior such as popping and jumping is avoided. In our model a dynamic label placement is a c ..."
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Cited by 14 (1 self)
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Map labeling encounters unique issues in the context of dynamic maps with continuous zooming and panning—an application with increasing practical importance. In consistent dynamic map labeling, distracting behavior such as popping and jumping is avoided. In our model a dynamic label placement is a
Results 11  20
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709,571