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Mobile Computing, Applications, and Services. 13th EAI International Conference, MobiCASE 2022, Messina, Italy, November 17-18, 2022, Proceedings

Research Article

Search by Pattern in GPS Trajectories

Cite
BibTeX Plain Text
  • @INPROCEEDINGS{10.1007/978-3-031-31891-7_9,
        author={Maros Cavojsky and Martin Drozda},
        title={Search by Pattern in GPS Trajectories},
        proceedings={Mobile Computing, Applications, and Services. 13th EAI International Conference, MobiCASE 2022, Messina, Italy, November 17-18, 2022, Proceedings},
        proceedings_a={MOBICASE},
        year={2023},
        month={4},
        keywords={GPS trajectory Geolife data set pattern search Needleman-Wunsch algorithm Smith-Waterman algorithm Geohash Hausdorff distance},
        doi={10.1007/978-3-031-31891-7_9}
    }
    
  • Maros Cavojsky
    Martin Drozda
    Year: 2023
    Search by Pattern in GPS Trajectories
    MOBICASE
    Springer
    DOI: 10.1007/978-3-031-31891-7_9
Maros Cavojsky1,*, Martin Drozda1
  • 1: Faculty of Electrical Engineering and Information Technology
*Contact email: maros.cavojsky@stuba.sk

Abstract

In search by pattern in GPS trajectories, user draws a trajectory, the pattern query, and then receives a set of trajectories ranked by their similarity to the pattern query. We argue that when user draws a pattern query, an initial part of this query (prefix of chosen length) should have more weight than the rest of query. We assume that after receiving a set of similar trajectories, user can refine the pattern query in order to receive more relevant results. We give explanation of our approach by means of web search, where a user searches, for example, for “bratislava castle” and then adds a refinement to this query “opening hours”, where removing the initial part of query does not make sense, as search for “opening hour” alone would return irrelevant results. This idea has led us to considering pattern search that is weighted toward query prefix. We experimentally evaluate this approach, in our experimentation we apply the Geolife data set (Microsoft Research Asia).

Keywords
GPS trajectory Geolife data set pattern search Needleman-Wunsch algorithm Smith-Waterman algorithm Geohash Hausdorff distance
Published
2023-04-29
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-031-31891-7_9
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