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Crowdsourced Social Data for Recommending Tourist Itineraries

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  • First Online:
Encyclopedia of Social Network Analysis and Mining

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Synonyms

Tourist trip design problem; Trip planning problem

Glossary

Crowdsourced data:

The data obtained by a crowdsourcing process, that is, by contributions (spontaneous or solicited) from a large group of people, especially an online community

Generalized Maximum Coverage Problem (GMCP):

is an extension of the classical Budgeted Maximum Coverage Problem. Given a cost budget B and a set of nondisjoint sets of items in E, where each item ei ∈ E is associated with a cost ci and a weight wi, the GMCP asks for selecting a subset of these sets such that the total weight of the items in the union of the chosen sets is maximized and the total cost of these items is lower than B

Itinerary (or sightseeing tour or simply tour):

is a detailed plan for a tourist journey, listing the PoIs to visit in a temporal sequence, possibly scheduled in the tourist agenda

Orienteering Problem (OP):

given a set of vertices V, where si is the score assigned to each vertex vi ∈ V, and tijis the time needed...

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References

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Acknowledgments

This work has been partially supported by SoBigData (GA. 654024) and BASMATI (GA. 723131) H2020 European projects.

Author information

Authors and Affiliations

  1. Federal University of Ceara, Fortaleza, Brazil

    Igo Ramalho Brilhante & Jose Antonio Macedo

  2. ISTI-CNR, Pisa, Italy

    Franco Maria Nardini & Raffaele Perego

  3. ISTI Institute of National Research Council, Pisa, Italy

    Chiara Renso

Authors
  1. Igo Ramalho Brilhante
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  2. Franco Maria Nardini
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  3. Jose Antonio Macedo
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  4. Raffaele Perego
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  5. Chiara Renso
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Corresponding author

Correspondence to Chiara Renso .

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Calgary, Calgary, AB, Canada

    Reda Alhajj

  2. Department of Computer Science, University of Calgary, Calgary, AB, Canada

    Jon Rokne

Section Editor information

  1. University of Technology Sydney, Sydney, Australia

    Guandong Xu

  2. Tsinghua University, 100084, Beijing, China

    Peng Cui

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Brilhante, I.R., Nardini, F.M., Macedo, J.A., Perego, R., Renso, C. (2018). Crowdsourced Social Data for Recommending Tourist Itineraries. In: Alhajj, R., Rokne, J. (eds) Encyclopedia of Social Network Analysis and Mining. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-7131-2_110202

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