Extracting Rankings for Spatial Keyword Queries from GPS Data

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

Abstract

Studies suggest that many search engine queries have local intent. We consider the evaluation of ranking functions important for such queries. The key challenge is to be able to determine the “best” ranking for a query, as this enables evaluation of the results of ranking functions. We propose a model that synthesizes a ranking of points of interest (PoI) for a given query using historical trips extracted from GPS data. To extract trips, we propose a novel PoI assignment method that makes use of distances and temporal information. We also propose a PageRank-based smoothing method to be able to answer queries for regions that are not covered well by trips. We report experimental results on a large GPS dataset that show that the proposed model is capable of capturing the visits of users to PoIs and of synthesizing rankings.
Original languageEnglish
Title of host publicationProgress in Location Based Services 2018
Number of pages22
PublisherSpringer
Publication date2018
Pages173-194
ISBN (Print)978-3-319-71469-1
ISBN (Electronic)978-3-319-71470-7
DOIs
Publication statusPublished - 2018
Event14th International Conference on Location Based Services - Zurich, Switzerland
Duration: 15 Jan 201817 Jan 2018
http://lbs18.ethz.ch/

Conference

Conference14th International Conference on Location Based Services
CountrySwitzerland
CityZurich
Period15/01/201817/01/2018
Internet address
SeriesLecture notes in geoinformation and Cartography
ISSN1863-2246

Fingerprint

Global positioning system
Search engines

Cite this

Keles, I., Jensen, C. S., & Saltenis, S. (2018). Extracting Rankings for Spatial Keyword Queries from GPS Data. In Progress in Location Based Services 2018 (pp. 173-194). Springer. Lecture notes in geoinformation and Cartography https://doi.org/10.1007/978-3-319-71470-7_9
Keles, Ilkcan ; Jensen, Christian Søndergaard ; Saltenis, Simonas. / Extracting Rankings for Spatial Keyword Queries from GPS Data. Progress in Location Based Services 2018. Springer, 2018. pp. 173-194 (Lecture notes in geoinformation and Cartography).
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Keles, I, Jensen, CS & Saltenis, S 2018, Extracting Rankings for Spatial Keyword Queries from GPS Data. in Progress in Location Based Services 2018. Springer, Lecture notes in geoinformation and Cartography, pp. 173-194, 14th International Conference on Location Based Services, Zurich, Switzerland, 15/01/2018. https://doi.org/10.1007/978-3-319-71470-7_9

Extracting Rankings for Spatial Keyword Queries from GPS Data. / Keles, Ilkcan; Jensen, Christian Søndergaard; Saltenis, Simonas.

Progress in Location Based Services 2018. Springer, 2018. p. 173-194.

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

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AB - Studies suggest that many search engine queries have local intent. We consider the evaluation of ranking functions important for such queries. The key challenge is to be able to determine the “best” ranking for a query, as this enables evaluation of the results of ranking functions. We propose a model that synthesizes a ranking of points of interest (PoI) for a given query using historical trips extracted from GPS data. To extract trips, we propose a novel PoI assignment method that makes use of distances and temporal information. We also propose a PageRank-based smoothing method to be able to answer queries for regions that are not covered well by trips. We report experimental results on a large GPS dataset that show that the proposed model is capable of capturing the visits of users to PoIs and of synthesizing rankings.

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Keles I, Jensen CS, Saltenis S. Extracting Rankings for Spatial Keyword Queries from GPS Data. In Progress in Location Based Services 2018. Springer. 2018. p. 173-194. (Lecture notes in geoinformation and Cartography). https://doi.org/10.1007/978-3-319-71470-7_9