Abstract
In this demonstration we re-visit the problem of finding an optimal route from location A to B. Currently, navigation systems compute shortest, fastest, most economic routes or any combination thereof. More often than not users want to consider “soft” qualitative metrics such as popularity, scenic value, and general appeal of a route. Routing algorithms have not (yet) been able to appreciate, measure, and evaluate such qualitative measures. Given the emergence of user-generated content, data exists that records user preference. This work exploits user-generated data, including image data, text data and trajectory data, to estimate the attractiveness of parts of the spatial network in relation to a particular user. We enrich the spatial network dataset by quantitative scores reflecting qualitative attractiveness. These scores are derived from a user-specific self-assessment (“On vacation I am interested in: family entertainment, cultural activities, exotic food”) and the selection of a respective subset of existing POIs. Using the enriched network, our demonstrator allows to perform a bicriterion optimal path search, which optimizes both travel time as well as the attractiveness of the route. Users will be able to choose from a whole skyline of alternative routes based on their preference. A chosen route will also be illustrated using user-generated data, such as images, textual narrative, and trajectories, i.e., data that showcase attractiveness and hopefully lead to a perfect trip.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsNotes
References
Andersen, O., Jensen, C.S., Torp, K., Yang, B.: Ecotour: reducing the environmental footprint of vehicles using eco-routes. In: MDM, pp. 338–340 (2013)
Graf, F., Kriegel, H.-P., Renz, M., Schubert, M.: MARiO: multi-attribute routing in open street map. In: Pfoser, D., Tao, Y., Mouratidis, K., Nascimento, M.A., Mokbel, M., Shekhar, S., Huang, Y. (eds.) SSTD 2011. LNCS, vol. 6849, pp. 486–490. Springer, Heidelberg (2011)
Shekelyan, M., Jossé, G., Schubert, M.: Linear path skylines in multicriteria networks. In: ICDE 2015, pp. 459–470 (2015)
Shekelyan, M., Jossé, G., Schubert, M.: Paretoprep: efficient lower bounds for path skylines and fast path computation. In: SSTD 2015 (2015)
Jossé, G., Franzke, M., Skoumas, G., Züfle, A., Nascimento, M.A., Renz, M.: A framework for computation of popular paths from crowdsourced data. In: ICDE, pp. 1428–1431 (2015)
Sacharidis, D., Bouros, P.: Routing directions: keeping it fast and simple. In: ACM SIGSPATIAL GIS, pp. 164–173 (2013)
Westphal, M., Renz, J.: Evaluating and minimizing ambiguities in qualitative route instructions. In: ACM SIGSPATIAL GIS, pp. 171–180 (2011)
Garcia, A., Arbelaitz, O., Linaza, M.T., Vansteenwegen, P., Souffriau, W.: Personalized tourist route generation. In: Daniel, F., Facca, F.M. (eds.) ICWE 2010. LNCS, vol. 6385, pp. 486–497. Springer, Heidelberg (2010)
Gavalas, D., Konstantopoulos, C., Mastakas, K., Pantziou, G.: A survey on algorithmic approaches for solving tourist trip design problems. J. Heuristics 20, 291–328 (2014)
Kanza, Y., Safra, E., Sagiv, Y., Doytsher, Y.: Heuristic algorithms for route-search queries over geographical data. In: ACM SIGSPATIAL GIS, p. 11 (2008)
Chen, H., Ku, W.S., Sun, M.T., Zimmermann, R.: The partial sequenced route query with traveling rules in road networks. Geoinformatica 15, 541–569 (2011)
Quercia, D., Schifanella, R., Aiello, L.M.: The shortest path to happiness: Recommending beautiful, quiet, and happy routes in the city. In: CoRR (abs/1407.1031) (2014)
Chen, Z., Shen, H.T., Zhou, X.: Discovering popular routes from trajectories. In: ICDE, pp. 900–911 (2011)
Newson, P., Krumm, J.: Hidden markov map matching through noise and sparseness. In: ACM SIGSPATIAL GIS, pp. 336–343 (2009)
Acknowledgements
This research has received funding from the Shared E-Fleet project (in the IKTII program) by the BMWi (grant no. 01ME12107), from the DFG (grant no. RE 266/5-1), from the DAAD supported by the BMBF (grant no. 57052426). Dieter Pfoser has been partially supported by NGA NURI (grant no. HM02101410004).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Jossé, G., Schmid, K.A., Züfle, A., Skoumas, G., Schubert, M., Pfoser, D. (2015). Tourismo: A User-Preference Tourist Trip Search Engine. In: Claramunt, C., et al. Advances in Spatial and Temporal Databases. SSTD 2015. Lecture Notes in Computer Science(), vol 9239. Springer, Cham. https://doi.org/10.1007/978-3-319-22363-6_32
Download citation
DOI: https://doi.org/10.1007/978-3-319-22363-6_32
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-22362-9
Online ISBN: 978-3-319-22363-6
eBook Packages: Computer ScienceComputer Science (R0)