Por onde quero ir? Interesses pessoais na escolha de um trajeto urbano
Abstract
When moving throughout the city, people may have different interests. Previous researches have considered user preferences to recommend paths and destinations. However, these preferences are generally related to time, distance and cost. In this paper, we assume that other personal and social interests can influence the path choice and should be considered in customized recommendation systems. Thus, this paper presents an exploratory study aiming to analyze what people consider as their interest while choosing the path. We conducted interviews and qualitatively analyzed the data by using open and axial coding. Our results evidenced that people have different interests in different contexts and aspects that influence the choice range from the landscape to the opinion of acquaintances about the path.
References
Adomavicius, G. and Tuzhilin, A. (2011). “Context-aware recommender systems”. Recommender systems handbook. Springer. p. 217–253.
Ballatore, A. and Bertolotto, M. (nov 2015). “Personalizing Maps”. Communications of ACM, v. 58, n. 12, p. 68–74.
Bao, J., Zheng, Y. and Mokbel, M. F. (2012). “Location-based and Preference-aware Recommendation Using Sparse Geo-social Networking Data”. In Proceedings of the 20th International Conference on Advances in Geographic Information Systems. , SIGSPATIAL ’12. ACM.
Bao, J., Zheng, Y., Wilkie, D. and Mokbel, M. (2015). “Recommendations in locationbased social networks: a survey”. GeoInformatica, v. 19, n. 3, p. 525–565.
Campigotto, P., Rudloff, C., Leodolter, M. and Bauer, D. (2016). “Personalized and situation-aware multimodal route recommendations: the FAVOUR algorithm”. CoRR, v. abs/1602.09076.
Cassiani, S. H. D. B., Caliri, M. H. L. and Pelá, N. T. R. (1996). A teoria fundamentada nos dados como abordagem da pesquisa interpretativa. Revista Latino-Americana de Enfermagem, v. 4, p. 75–88.
Chen, C., Zhang, D., Guo, B., et al. (2015). “TripPlanner: Personalized Trip Planning Leveraging Heterogeneous Crowdsourced Digital Footprints”. IEEE Transactions on Intelligent Transportation Systems, v. 16, n. 3, p. 1259–1273.
Corbin, J. and Strauss, A. (2014). “Basics of qualitative research: Techniques and procedures for developing grounded theory”. Sage publications.
Kurashima, T., Iwata, T., Irie, G. and Fujimura, K. (2012). “Travel route recommendation using geotagged photos”. Knowledge and Information Systems, v. 37, n. 1, p. 37–60.
Pires, C. S., Aguiar, M. S. De and Ferreira, P. R. (2015). “Mobile ACORoute-Route Recommendation Based on Communication by Pheromones”. Polibits, n. 51, p. 27–32.
Su, H., Zheng, K., Huang, J., et al. (2014). “Crowdplanner: A crowd-based route recommendation system”. In Data Engineering (ICDE), 2014 IEEE 30th International Conference on. . IEEE.
Tsai, C. Y. and Lai, B. H. (2013). “A Customized Visiting Route Service under RFID Environment”. In Computer Software and Applications Conference Workshops (COMPSACW), 2013 IEEE 37th Annual.
Tsai, C.-Y. and Chung, S.-H. (2012). “A personalized route recommendation service for theme parks using {RFID} information and tourist behavior”. Decision Support Systems, v. 52, n. 2, p. 514–527.
Yang, B., Guo, C., Ma, Y. and Jensen, C. S. (2015). “Toward Personalized, Contextaware Routing”. The VLDB Journal, v. 24, n. 2, p. 297–318.
