A Mobile Trusted Path System Based on Social Network Data

Félix Mata; Roberto Zagal-Flores; Jacobo González León; Christophe Claramunt

doi:10.1007/978-3-030-60952-8_17

A Mobile Trusted Path System Based on Social Network Data

Félix Mata, Roberto Zagal-Flores, Jacobo González León, Christophe Claramunt

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

Abstract

Social networks provide rich data sources for analyzing people journeys in urban environments. This paper introduces a trusted path system that helps users to find their routes based in low crime rate and theft reports. These data are obtained geo-tagged tweets and an official database. Recommended paths are computed automatically from these data sources by a complementary application of social mining techniques, Bayes algorithm and an adaptation of the Dijkstra algorithm. This system can be also used to identify the probability that an event occurs in specific locations and times. A proof of concept of the system is illustrated through two example scenarios.

Original language	English
Title of host publication	Web and Wireless Geographical Information Systems - 18th International Symposium, W2GIS 2020, Proceedings
Editors	Sergio Di Martino, Zhixiang Fang, Ki-Joune Li
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	166-170
Number of pages	5
ISBN (Print)	9783030609511
DOIs	https://doi.org/10.1007/978-3-030-60952-8_17
State	Published - 2020
Event	18th International Symposium on Web and Wireless Geographical Information Systems, W2GIS 2019 - Wuhan, China Duration: 13 Nov 2020 → 14 Nov 2020

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12473 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	18th International Symposium on Web and Wireless Geographical Information Systems, W2GIS 2019
Country/Territory	China
City	Wuhan
Period	13/11/20 → 14/11/20

Keywords

Outdoor navigation
Recommender systems
Trusted paths

Access to Document

10.1007/978-3-030-60952-8_17

Cite this

Mata, F., Zagal-Flores, R., León, J. G., & Claramunt, C. (2020). A Mobile Trusted Path System Based on Social Network Data. In S. Di Martino, Z. Fang, & K.-J. Li (Eds.), Web and Wireless Geographical Information Systems - 18th International Symposium, W2GIS 2020, Proceedings (pp. 166-170). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12473 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-60952-8_17

Mata, Félix ; Zagal-Flores, Roberto ; León, Jacobo González et al. / A Mobile Trusted Path System Based on Social Network Data. Web and Wireless Geographical Information Systems - 18th International Symposium, W2GIS 2020, Proceedings. editor / Sergio Di Martino ; Zhixiang Fang ; Ki-Joune Li. Springer Science and Business Media Deutschland GmbH, 2020. pp. 166-170 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Social networks provide rich data sources for analyzing people journeys in urban environments. This paper introduces a trusted path system that helps users to find their routes based in low crime rate and theft reports. These data are obtained geo-tagged tweets and an official database. Recommended paths are computed automatically from these data sources by a complementary application of social mining techniques, Bayes algorithm and an adaptation of the Dijkstra algorithm. This system can be also used to identify the probability that an event occurs in specific locations and times. A proof of concept of the system is illustrated through two example scenarios.",

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Mata, F , Zagal-Flores, R, León, JG & Claramunt, C 2020, A Mobile Trusted Path System Based on Social Network Data. in S Di Martino, Z Fang & K-J Li (eds), Web and Wireless Geographical Information Systems - 18th International Symposium, W2GIS 2020, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12473 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 166-170, 18th International Symposium on Web and Wireless Geographical Information Systems, W2GIS 2019, Wuhan, China, 13/11/20. https://doi.org/10.1007/978-3-030-60952-8_17

A Mobile Trusted Path System Based on Social Network Data. / Mata, Félix ; Zagal-Flores, Roberto; León, Jacobo González et al.
Web and Wireless Geographical Information Systems - 18th International Symposium, W2GIS 2020, Proceedings. ed. / Sergio Di Martino; Zhixiang Fang; Ki-Joune Li. Springer Science and Business Media Deutschland GmbH, 2020. p. 166-170 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12473 LNCS).

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

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T1 - A Mobile Trusted Path System Based on Social Network Data

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AU - Zagal-Flores, Roberto

AU - León, Jacobo González

AU - Claramunt, Christophe

PY - 2020

Y1 - 2020

N2 - Social networks provide rich data sources for analyzing people journeys in urban environments. This paper introduces a trusted path system that helps users to find their routes based in low crime rate and theft reports. These data are obtained geo-tagged tweets and an official database. Recommended paths are computed automatically from these data sources by a complementary application of social mining techniques, Bayes algorithm and an adaptation of the Dijkstra algorithm. This system can be also used to identify the probability that an event occurs in specific locations and times. A proof of concept of the system is illustrated through two example scenarios.

AB - Social networks provide rich data sources for analyzing people journeys in urban environments. This paper introduces a trusted path system that helps users to find their routes based in low crime rate and theft reports. These data are obtained geo-tagged tweets and an official database. Recommended paths are computed automatically from these data sources by a complementary application of social mining techniques, Bayes algorithm and an adaptation of the Dijkstra algorithm. This system can be also used to identify the probability that an event occurs in specific locations and times. A proof of concept of the system is illustrated through two example scenarios.

KW - Outdoor navigation

KW - Recommender systems

KW - Trusted paths

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M3 - Contribución a la conferencia

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Y2 - 13 November 2020 through 14 November 2020

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Mata F , Zagal-Flores R, León JG, Claramunt C. A Mobile Trusted Path System Based on Social Network Data. In Di Martino S, Fang Z, Li KJ, editors, Web and Wireless Geographical Information Systems - 18th International Symposium, W2GIS 2020, Proceedings. Springer Science and Business Media Deutschland GmbH. 2020. p. 166-170. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-60952-8_17

A Mobile Trusted Path System Based on Social Network Data

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