Orienteering or itinerary planning applications aim to optimize travel routes exploiting user preference and other constraints, such as time budget or traffic conditions. For these algorithms, it is essential to explore the user preference to predict potential Points-Of-Interest (POI) or touristic routes. However, user preference has been significantly affected by the COVID-19, since health concern plays a key trade-off role now. For example, people may try to avoid crowdedness, even if there is a strong social desire. However, most orienteering applications just focus on user preferences, thus paying less attention to the variety of the data inputs, which has become an essential factor for the utility of the application in the COVID-19 era. Therefore, this paper proposes a social sensing system that considers the trade-off between user preference and various factors, such as crowdedness, fear of being infected, knowledge of the COVID-19, POI features, and desire for socialization. The experiments are conducted on profiling user interests with Doc2Vec and FastText based on the Yelp dataset. Furthermore, the proposed system is modular and can be efficiently adapted to different applications for COVID-aware itinerary planning.

Pilato, G., Persia, F., Ge, M., D'Auria, D. (2022). Social Sensing for Personalized Orienteering Mediating the Need for Sociality and the Risk of COVID-19. IEEE TRANSACTIONS ON TECHNOLOGY AND SOCIETY, 3(4 (December 2022)), 323-332 [10.1109/TTS.2022.3210882].

Social Sensing for Personalized Orienteering Mediating the Need for Sociality and the Risk of COVID-19

D'Auria, D
2022

Abstract

Orienteering or itinerary planning applications aim to optimize travel routes exploiting user preference and other constraints, such as time budget or traffic conditions. For these algorithms, it is essential to explore the user preference to predict potential Points-Of-Interest (POI) or touristic routes. However, user preference has been significantly affected by the COVID-19, since health concern plays a key trade-off role now. For example, people may try to avoid crowdedness, even if there is a strong social desire. However, most orienteering applications just focus on user preferences, thus paying less attention to the variety of the data inputs, which has become an essential factor for the utility of the application in the COVID-19 era. Therefore, this paper proposes a social sensing system that considers the trade-off between user preference and various factors, such as crowdedness, fear of being infected, knowledge of the COVID-19, POI features, and desire for socialization. The experiments are conducted on profiling user interests with Doc2Vec and FastText based on the Yelp dataset. Furthermore, the proposed system is modular and can be efficiently adapted to different applications for COVID-aware itinerary planning.
Articolo in rivista - Articolo scientifico
Social sensing, orienteering, crowdedness avoidance, sentiment analysis, contagion prevention
English
29-set-2022
2022
3
4 (December 2022)
323
332
none
Pilato, G., Persia, F., Ge, M., D'Auria, D. (2022). Social Sensing for Personalized Orienteering Mediating the Need for Sociality and the Risk of COVID-19. IEEE TRANSACTIONS ON TECHNOLOGY AND SOCIETY, 3(4 (December 2022)), 323-332 [10.1109/TTS.2022.3210882].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/468038
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