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SSD
2007
Springer

Computing a k -Route over Uncertain Geographical Data

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Computing a k -Route over Uncertain Geographical Data
An uncertain geo-spatial dataset is a collection of geo-spatial objects that do not represent accurately real-world entities. Each object has a confidence value indicating how likely it is for the object to be correct. Uncertain data can be the result of operations such as imprecise integration, incorrect update or inexact querying. A k-route, over an uncertain geo-spatial dataset, is a path that travels through the geo-spatial objects, starting at a given location and stopping after visiting k correct objects. A k-route is considered shortest if the expected length of the route is less than or equal to the expected length of any other k-route that starts at the given location. This paper introduces the problem of finding a shortest k-route over an uncertain dataset. Since the problem is a generalization of the traveling salesman problem, it is unlikely to have an efficient solution, i.e., there is no polynomial-time algorithm that solves the problem (unless P=NP). Hence, in this wo...
Eliyahu Safra, Yaron Kanza, Nir Dolev, Yehoshua Sa
Added 09 Jun 2010
Updated 09 Jun 2010
Type Conference
Year 2007
Where SSD
Authors Eliyahu Safra, Yaron Kanza, Nir Dolev, Yehoshua Sagiv, Yerach Doytsher
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