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167
Bidirectional Expansion For Keyword Search On Graph Databases
, 2005
"... Relational, XML and HTML data can be represented as graphs with entities as nodes and relationships as edges. Text is associated with nodes and possibly edges. Keyword search on such graphs has received much attention lately. A central problem in this scenario is to e#ciently extract from the ..."
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Cited by 155 (5 self)
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Relational, XML and HTML data can be represented as graphs with entities as nodes and relationships as edges. Text is associated with nodes and possibly edges. Keyword search on such graphs has received much attention lately. A central problem in this scenario is to e#ciently extract from the data graph a small number of the "best" answer trees. A Backward Expanding search, starting at nodes matching keywords and working up toward confluent roots, is commonly used for predominantly textdriven queries. But it can perform poorly if some keywords match many nodes, or some node has very large degree. In this paper
Fast exact and approximate geodesics on meshes
 ACM Trans. Graph
, 2005
"... The computation of geodesic paths and distances on triangle meshes is a common operation in many computer graphics applications. We present several practical algorithms for computing such geodesics from a source point to one or all other points efficiently. First, we describe an implementation of th ..."
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Cited by 102 (0 self)
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The computation of geodesic paths and distances on triangle meshes is a common operation in many computer graphics applications. We present several practical algorithms for computing such geodesics from a source point to one or all other points efficiently. First, we describe an implementation of the exact “single source, all destination ” algorithm presented by Mitchell, Mount, and Papadimitriou (MMP). We show that the algorithm runs much faster in practice than suggested by worst case analysis. Next, we extend the algorithm with a merging operation to obtain computationally efficient and accurate approximations with bounded error. Finally, to compute the shortest path between two given points, we use a lowerbound property of our approximate geodesic algorithm to efficiently prune the frontier of the MMP algorithm, thereby obtaining an exact solution even more quickly.
Scalable Network Distance Browsing in Spatial Databases
, 2008
"... An algorithm is presented for finding the k nearest neighbors in a spatial network in a bestfirst manner using network distance. The algorithm is based on precomputing the shortest paths between all possible vertices in the network and then making use of an encoding that takes advantage of the fact ..."
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Cited by 84 (10 self)
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An algorithm is presented for finding the k nearest neighbors in a spatial network in a bestfirst manner using network distance. The algorithm is based on precomputing the shortest paths between all possible vertices in the network and then making use of an encoding that takes advantage of the fact that the shortest paths from vertex u to all of the remaining vertices can be decomposed into subsets based on the first edges on the shortest paths to them from u. Thus, in the worst case, the amount of work depends on the number of objects that are examined and the number of links on the shortest paths to them from q, rather than depending on the number of vertices in the network. The amount of storage required to keep track of the subsets is reduced by taking advantage of their spatial coherence which is captured by the aid of a shortest path quadtree. In particular, experiments on a number of large road networks as
Engineering Route Planning Algorithms
 ALGORITHMICS OF LARGE AND COMPLEX NETWORKS. LECTURE NOTES IN COMPUTER SCIENCE
, 2009
"... Algorithms for route planning in transportation networks have recently undergone a rapid development, leading to methods that are up to three million times faster than Dijkstra’s algorithm. We give an overview of the techniques enabling this development and point out frontiers of ongoing research on ..."
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Cited by 82 (39 self)
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Algorithms for route planning in transportation networks have recently undergone a rapid development, leading to methods that are up to three million times faster than Dijkstra’s algorithm. We give an overview of the techniques enabling this development and point out frontiers of ongoing research on more challenging variants of the problem that include dynamically changing networks, timedependent routing, and flexible objective functions.
Reach for A∗: Efficient PointtoPoint Shortest Path Algorithms
, 2006
"... We study the pointtopoint shortest path problem in a setting where preprocessing is allowed. We improve the reachbased approach of Gutman [17] in several ways. In particular, we introduce a bidirectional version of the algorithm that uses implicit lower bounds and we add shortcut arcs to reduce v ..."
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Cited by 77 (6 self)
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We study the pointtopoint shortest path problem in a setting where preprocessing is allowed. We improve the reachbased approach of Gutman [17] in several ways. In particular, we introduce a bidirectional version of the algorithm that uses implicit lower bounds and we add shortcut arcs to reduce vertex reaches. Our modifications greatly improve both preprocessing and query times. The resulting algorithm is as fast as the best previous method, due to Sanders and Schultes [28]. However, our algorithm is simpler and combines in a natural way with A∗ search, which yields significantly better query times.
Combining Hierarchical and GoalDirected SpeedUp Techniques for Dijkstra’s Algorithm
 PROCEEDINGS OF THE 7TH WORKSHOP ON EXPERIMENTAL ALGORITHMS (WEA’08), VOLUME 5038 OF LECTURE NOTES IN COMPUTER SCIENCE
, 2008
"... In recent years, highly effective hierarchical and goaldirected speedup techniques for routing in large road networks have been developed. This paper makes a systematic study of combinations of such techniques. These combinations turn out to give the best results in many scenarios, including graphs ..."
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Cited by 60 (24 self)
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In recent years, highly effective hierarchical and goaldirected speedup techniques for routing in large road networks have been developed. This paper makes a systematic study of combinations of such techniques. These combinations turn out to give the best results in many scenarios, including graphs for unit disk graphs, grid networks, and timeexpanded timetables. Besides these quantitative results, we obtain general insights for successful combinations.
Mapmatching for lowsamplingrate GPS trajectories
 In Proc. ACM SIGSPATIAL GIS
, 2009
"... Mapmatching is the process of aligning a sequence of observed user positions with the road network on a digital map. It is a fundamental preprocessing step for many applications, such as moving object management, traffic flow analysis, and driving directions. In practice there exists huge amount o ..."
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Cited by 54 (7 self)
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Mapmatching is the process of aligning a sequence of observed user positions with the road network on a digital map. It is a fundamental preprocessing step for many applications, such as moving object management, traffic flow analysis, and driving directions. In practice there exists huge amount of lowsamplingrate (e.g., one point every 25 minutes) GPS trajectories. Unfortunately, most current mapmatching approaches only deal with highsamplingrate (typically one point every 1030s) GPS data, and become less effective for lowsamplingrate points as the uncertainty in data increases. In this paper, we propose a novel global mapmatching algorithm called STMatching for lowsamplingrate GPS trajectories. STMatching considers (1) the spatial geometric and topological structures of the road network and (2) the temporal/speed constraints of the trajectories. Based on spatiotemporal analysis, a candidate graph is constructed from which the best matching path sequence is identified. We compare STMatching with the incremental algorithm and AverageFréchetDistance (AFD) based global mapmatching algorithm. The experiments are performed both on synthetic and real dataset. The results show that our STmatching algorithm significantly outperform incremental algorithm in terms of matching accuracy for lowsampling trajectories. Meanwhile, when compared with AFDbased global algorithm, STMatching also improves accuracy as well as running time.
Computing PointtoPoint Shortest Paths from External Memory
"... We study the ALT algorithm [19] for the pointtopoint shortest path problem in the context of road networks. We suggest improvements to the algorithm itself and to its preprocessing stage. We also develop a memoryefficient implementation of the algorithm that runs on a Pocket PC. It stores graph d ..."
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Cited by 54 (6 self)
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We study the ALT algorithm [19] for the pointtopoint shortest path problem in the context of road networks. We suggest improvements to the algorithm itself and to its preprocessing stage. We also develop a memoryefficient implementation of the algorithm that runs on a Pocket PC. It stores graph data in a flash memory card and uses RAM to store information only for the part of the graph visited by the current shortest path computation. The implementation works even on very large graphs, including that of the North America road network, with almost 30 million vertices.