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...

• Type: Conference
• Year: 2007
• Where: SSD
• Authors: Eliyahu Safra, Yaron Kanza, Nir Dolev, Yehoshua Sagiv, Yerach Doytsher
• Keywords: Geo-spatial Objects, SSD 2007, Uncertain Data, Uncertain Geo-spatial Dataset