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SSD

2007

Springer

2007

Springer

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...

Related Content

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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