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Titlebook: Spatial and Temporal Databases; 13th International S Mario A. Nascimento,Timos Sellis,Christian Sengsto Conference proceedings 2013 Springe

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樓主: detumescence
21#
發(fā)表于 2025-3-25 06:52:11 | 只看該作者
Capacity-Constrained Network-Voronoi Diagram: A Summary of Resultsce areas that meet service center capacities and minimize the sum of the distances (min-sum) from graph-nodes to allotted service centers. The CCNVD problem is important for critical societal applications such as assigning evacuees to shelters and assigning patients to hospitals. This problem is NP-
22#
發(fā)表于 2025-3-25 09:37:36 | 只看該作者
23#
發(fā)表于 2025-3-25 14:42:36 | 只看該作者
24#
發(fā)表于 2025-3-25 19:54:24 | 只看該作者
Discovering Influential Data Objects over Timegnificant number of customers. However, customer preferences change over time, and product manufacturers are interested in monitoring the evolution of the popularity of their products, in order to discover those products that are consistently highly ranked. To take into account the temporal dimensio
25#
發(fā)表于 2025-3-25 20:09:33 | 只看該作者
Finding Traffic-Aware Fastest Paths in Spatial Networksfinding traffic-aware fastest paths (TAFP query) in spatial networks by considering the related traffic conditions. Given a sequence of user specified intended places .. and a departure time ., TAFP finds the fastest path connecting .. in order to guarantee that moving objects (e.g., travelers and b
26#
發(fā)表于 2025-3-26 01:51:45 | 只看該作者
27#
發(fā)表于 2025-3-26 07:46:15 | 只看該作者
28#
發(fā)表于 2025-3-26 11:46:32 | 只看該作者
PL-Tree: An Efficient Indexing Method for High-Dimensional Dataethod for a given set of data requires careful consideration of data properties, data construction methods, and query types. We present a new indexing method to support efficient point queries, range queries, and .-nearest neighbor queries. Our method indexes objects dynamically using algebraic tech
29#
發(fā)表于 2025-3-26 15:41:52 | 只看該作者
30#
發(fā)表于 2025-3-26 20:21:46 | 只看該作者
Best Upgrade Plans for Large Road Networkswork (weighted graph) . where a subset of the edges are ., i.e., for each such edge there is a cost, which if spent, the weight of the edge can be reduced to a specific new value. Given a source and a destination in ., and a budget (resource constraint) ., the BUP problem is to identify which upgrad
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