TY - GEN
T1 - Heuristic algorithms for route-search queries over geographical data
AU - Kanza, Yaron
AU - Safra, Eliyahu
AU - Sagiv, Yehoshua
AU - Doytsher, Yerach
PY - 2008
Y1 - 2008
N2 - In a geographical route search, given search terms, the goal is to find an effective route that (1) starts at a given location, (2) ends at a given location, and (3) travels via geographical entities that are relevant to the given terms. A route is effective if it does not exceed a given distance limit whereas the ranking scores of the visited entities, with respect to the search terms, are maximal. This paper introduces route-search queries, suggests three semantics for such queries and deals with the problem of e ciently answering queries under the different semantics. Since the problem of answering route-search queries is a generalization of the traveling salesman problem, it is unlikely to have an e cient solution, i.e., there is no polynomial-time algorithm that solves the problem (unless P=NP). Hence, in this work we consider heuristics for the problem. Methods for effectively computing routes are presented. The methods are compared analytically and experimentally. For these methods, experiments on both synthetic and real-world data illustrate their efficiency and their effectiveness in computing a route that satisfies the constraints of a route-search query.
AB - In a geographical route search, given search terms, the goal is to find an effective route that (1) starts at a given location, (2) ends at a given location, and (3) travels via geographical entities that are relevant to the given terms. A route is effective if it does not exceed a given distance limit whereas the ranking scores of the visited entities, with respect to the search terms, are maximal. This paper introduces route-search queries, suggests three semantics for such queries and deals with the problem of e ciently answering queries under the different semantics. Since the problem of answering route-search queries is a generalization of the traveling salesman problem, it is unlikely to have an e cient solution, i.e., there is no polynomial-time algorithm that solves the problem (unless P=NP). Hence, in this work we consider heuristics for the problem. Methods for effectively computing routes are presented. The methods are compared analytically and experimentally. For these methods, experiments on both synthetic and real-world data illustrate their efficiency and their effectiveness in computing a route that satisfies the constraints of a route-search query.
KW - Approximation algorithms
KW - Geographic information system
KW - Heuristic algorithms
KW - Path
KW - Route
KW - Search
UR - http://www.scopus.com/inward/record.url?scp=70449719464&partnerID=8YFLogxK
U2 - 10.1145/1463434.1463449
DO - 10.1145/1463434.1463449
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AN - SCOPUS:70449719464
SN - 9781605583235
T3 - GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems
SP - 75
EP - 84
BT - Proceedings of the 16th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM GIS 2008
T2 - 16th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM GIS 2008
Y2 - 5 November 2008 through 7 November 2008
ER -