Spatiotemporal Behavior Profiling: A Treasure Hunt Case Study

V. de Graaff; Dieter Pfoser; Maurice van Keulen; R.A. de By

doi:10.1007/978-3-319-18251-3_9

Spatiotemporal Behavior Profiling: A Treasure Hunt Case Study

V. de Graaff, Dieter Pfoser, Maurice van Keulen, R.A. de By

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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Abstract

Trajectories have been providing us with a wealth of derived information such as traffic conditions and road network updates. This work focuses on deriving user profiles through spatiotemporal analysis of trajectory data to provide insight into the quality of information provided by users. The presented behavior profiling method assesses user participation characteristics in a treasure-hunt type event. Consisting of an analysis and a profiling phase, analysis involves a timeline and a stay-point analysis, as well as a semantic trajectory inspection relating actual and expected paths. The analysis results are then grouped around profiles that can be used to estimate the user performance in the activity. The proposed profiling method is evaluated by means of a student orientation treasure-hunt activity at the University of Twente, The Netherlands. The profiling method is used to predict the students' gaming behavior by means of a simple team type classification, and a feature-based answer type classification.

Original language	English
Title of host publication	Web and Wireless Geographical Information Systems
Subtitle of host publication	14th International Symposium, W2GIS 2015, Grenoble, France, May 21-22, 2015, Proceedings
Editors	Jérôme Gensel, Martin Tomko
Place of Publication	Berlin
Publisher	Springer
Pages	143-158
Number of pages	16
ISBN (Electronic)	978-3-319-18251-3
ISBN (Print)	978-3-319-18250-6
DOIs	https://doi.org/10.1007/978-3-319-18251-3_9
Publication status	Published - 21 May 2015
Event	14th Web and Wireless Geographical Information Systems, W2GIS 2015 - Grenoble, France Duration: 21 May 2015 → 22 May 2015 Conference number: 14

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer
Volume	9080

Conference

Conference	14th Web and Wireless Geographical Information Systems, W2GIS 2015
Abbreviated title	W2GIS 2015
Country/Territory	France
City	Grenoble
Period	21/05/15 → 22/05/15

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10.1007/978-3-319-18251-3_9

ArticleAccepted author version, 6.16 MB

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de Graaff, V., Pfoser, D., van Keulen, M., & de By, R. A. (2015). Spatiotemporal Behavior Profiling: A Treasure Hunt Case Study. In J. Gensel, & M. Tomko (Eds.), Web and Wireless Geographical Information Systems: 14th International Symposium, W2GIS 2015, Grenoble, France, May 21-22, 2015, Proceedings (pp. 143-158). (Lecture Notes in Computer Science; Vol. 9080). Springer. https://doi.org/10.1007/978-3-319-18251-3_9

de Graaff, V. ; Pfoser, Dieter ; van Keulen, Maurice et al. / Spatiotemporal Behavior Profiling : A Treasure Hunt Case Study. Web and Wireless Geographical Information Systems: 14th International Symposium, W2GIS 2015, Grenoble, France, May 21-22, 2015, Proceedings. editor / Jérôme Gensel ; Martin Tomko. Berlin : Springer, 2015. pp. 143-158 (Lecture Notes in Computer Science).

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title = "Spatiotemporal Behavior Profiling: A Treasure Hunt Case Study",

abstract = "Trajectories have been providing us with a wealth of derived information such as traffic conditions and road network updates. This work focuses on deriving user profiles through spatiotemporal analysis of trajectory data to provide insight into the quality of information provided by users. The presented behavior profiling method assesses user participation characteristics in a treasure-hunt type event. Consisting of an analysis and a profiling phase, analysis involves a timeline and a stay-point analysis, as well as a semantic trajectory inspection relating actual and expected paths. The analysis results are then grouped around profiles that can be used to estimate the user performance in the activity. The proposed profiling method is evaluated by means of a student orientation treasure-hunt activity at the University of Twente, The Netherlands. The profiling method is used to predict the students' gaming behavior by means of a simple team type classification, and a feature-based answer type classification.",

author = "{de Graaff}, V. and Dieter Pfoser and {van Keulen}, Maurice and {de By}, R.A.",

year = "2015",

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de Graaff, V, Pfoser, D, van Keulen, M & de By, RA 2015, Spatiotemporal Behavior Profiling: A Treasure Hunt Case Study. in J Gensel & M Tomko (eds), Web and Wireless Geographical Information Systems: 14th International Symposium, W2GIS 2015, Grenoble, France, May 21-22, 2015, Proceedings. Lecture Notes in Computer Science, vol. 9080, Springer, Berlin, pp. 143-158, 14th Web and Wireless Geographical Information Systems, W2GIS 2015, Grenoble, France, 21/05/15. https://doi.org/10.1007/978-3-319-18251-3_9

Spatiotemporal Behavior Profiling: A Treasure Hunt Case Study. / de Graaff, V.; Pfoser, Dieter; van Keulen, Maurice et al.
Web and Wireless Geographical Information Systems: 14th International Symposium, W2GIS 2015, Grenoble, France, May 21-22, 2015, Proceedings. ed. / Jérôme Gensel; Martin Tomko. Berlin: Springer, 2015. p. 143-158 (Lecture Notes in Computer Science; Vol. 9080).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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PY - 2015/5/21

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N2 - Trajectories have been providing us with a wealth of derived information such as traffic conditions and road network updates. This work focuses on deriving user profiles through spatiotemporal analysis of trajectory data to provide insight into the quality of information provided by users. The presented behavior profiling method assesses user participation characteristics in a treasure-hunt type event. Consisting of an analysis and a profiling phase, analysis involves a timeline and a stay-point analysis, as well as a semantic trajectory inspection relating actual and expected paths. The analysis results are then grouped around profiles that can be used to estimate the user performance in the activity. The proposed profiling method is evaluated by means of a student orientation treasure-hunt activity at the University of Twente, The Netherlands. The profiling method is used to predict the students' gaming behavior by means of a simple team type classification, and a feature-based answer type classification.

AB - Trajectories have been providing us with a wealth of derived information such as traffic conditions and road network updates. This work focuses on deriving user profiles through spatiotemporal analysis of trajectory data to provide insight into the quality of information provided by users. The presented behavior profiling method assesses user participation characteristics in a treasure-hunt type event. Consisting of an analysis and a profiling phase, analysis involves a timeline and a stay-point analysis, as well as a semantic trajectory inspection relating actual and expected paths. The analysis results are then grouped around profiles that can be used to estimate the user performance in the activity. The proposed profiling method is evaluated by means of a student orientation treasure-hunt activity at the University of Twente, The Netherlands. The profiling method is used to predict the students' gaming behavior by means of a simple team type classification, and a feature-based answer type classification.

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de Graaff V, Pfoser D, van Keulen M , de By RA. Spatiotemporal Behavior Profiling: A Treasure Hunt Case Study. In Gensel J, Tomko M, editors, Web and Wireless Geographical Information Systems: 14th International Symposium, W2GIS 2015, Grenoble, France, May 21-22, 2015, Proceedings. Berlin: Springer. 2015. p. 143-158. (Lecture Notes in Computer Science). doi: 10.1007/978-3-319-18251-3_9

Spatiotemporal Behavior Profiling: A Treasure Hunt Case Study

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