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Productive Networks and Indirect Locations

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Part of the Geotechnologies and the Environment book series (GEOTECH,volume 18)

Abstract

Discovering interesting locations to users is a challenge for social and productive networks. The evidence of the content produced by users must be considered in this task, which may be simplified by the use of the metadata associated with the content, i.e., the categorization supported by the network, namely – descriptive keywords and geographic coordinates. In this book chapter we present a productive network representation model, designed to discover indirect keywords and locations. The spatial dimension of the model enables indirect location discovery methods through the interpretation of the network as a graph, solely relying on keywords and locations that categorize or describe productive items. The model and indirect location discovery methodology presented in this chapter avoid content analysis, and are a new step towards a generic approach to the identification of relevant information, otherwise hidden from the users. The evaluation of the model and methods is accomplished by an experiment that performs a classification analysis over the Twitter network.

Keywords

  • Data mining
  • Location recommendation
  • Social networks
  • Productive networks

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Fig. 5.1
Fig. 5.2
Fig. 5.3
Fig. 5.4

Notes

  1. 1.

    http://www.wikipedia.com

  2. 2.

    https://www.facebook.com

  3. 3.

    https://plus.google.com

  4. 4.

    https://www.flickr.com

  5. 5.

    https://www.instagram.com

  6. 6.

    http://portal.acm.org

  7. 7.

    http://ieeexplore.ieee.org

  8. 8.

    https://en.wikipedia.org/wiki/List_of_social_networking_websites

  9. 9.

    http://www.alexa.com/topsites

References

  • Eisenberg AF, Houser J (2007) Social network theory. In: Ritzer G (ed) Encyclopedia of sociology. Blackwell Pub., Malden, pp 4492:4

    Google Scholar 

  • Ester M, Kriegel H, Sander J, Xu X (1996) A density-based algorithm for discovering clusters in large spatial databases with noise. In: Proceedings of 2nd International Conference on Knowledge Discovery and Data Mining

    Google Scholar 

  • Ference G, Ye M, Lee W-c (2013) Location recommendation for out-of-town users in location-based social networks. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, San Francisco, pp 721–726

    Google Scholar 

  • Fortes C, Reis M, Poseiro P, Capitão R, Santos J, Pinheiro L, Craveiro J, Rodrigues A, Sabino A, Silva SF, Ferreira J, Raposeiro P, Silva C, Rodrigues M, Simões A, Azevedo E, Reis F (2014a) HIDRALERTA Project – a flood forecast and alert system in coastal and port areas. In: Proceedings of the IWA World Water Congress and Exhibition, Lisbon

    Google Scholar 

  • Fortes C, Reis M, Poseiro P, Capitão R, Santos J, Pinheiro L, Rodrigues A, Sabino A, Rodrigues M, Raposeiro P, Ferreira J, Silva C, Simões A, Azevedo E (2014b) O Projeto HIDRALERTA – Sistema de previsão e alerta de inundações em zonas costeiras e portuárias. In: Proceedings of the 8th Jornadas Portuguesas de Engenharia Costeira e Portuária, Lisbon

    Google Scholar 

  • Fortes CJ, Reis MT, Poseiro P, Santos JA, Garcia T, Capitão R, Pinheiro L, Reis R, Craveiro J, Lourenço I, Lopes P, Rodrigues A, Sabino A, Ferreira JC, Silva S, Raposeiro P, Simões A, Azevedo EB, Vieira F, Rodrigues MDC, Silva CP (2015) Ferramenta de apoio à gestão costeira e portuária: o sistema hidralerta. In: Proceedings of the VIII Congresso sobre Planeamento e Gestão das Zonas Costeiras dos Países de Expressão Portuguesa, pp 1–18

    Google Scholar 

  • Ho S, Lieberman M, Wang P, Samet H (2012) Mining future spatiotemporal events and their sentiment from online news articles for location-aware recommendation system. In: Proceedings of the First ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems, Redondo Beach, pp 25–32

    Google Scholar 

  • Hu B, Ester M (2013) Spatial topic modeling in online social media for location recommendation. In: Proceedings of the 7th ACM Conference on Recommender Systems, Hong Kong, pp 25–32

    Google Scholar 

  • Laere OV, Schockaert S, Dhoedt B (2010) Towards automated georeferencing of Flickr photos. In: Proceedings of the 6th Workshop on Geographic Information Retrieval, Zurich

    Google Scholar 

  • Leskovec J, Faloutsos C (2006) Sampling from large graphs. In: Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Philadelphia

    Google Scholar 

  • Leskovec J, Kleinberg J, Faloutsos C, Management HD, Applications D (2005) Graphs over time: densification laws, shrinking diameters and possible explanations. In: Proceeding of the 11th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM Press, New York, pp 177–187

    Google Scholar 

  • Ozdikis O, Oguztuzun H, Karagoz P (2013) Evidential location estimation for events detected in Twitter. In: Proceedings of the 7th Workshop on Geographic Information Retrieval, Orlando, pp 9–16

    Google Scholar 

  • Peregrino F, Tomás D, Llopis F (2013) Every move you make I’ll be watching you: geographical focus detection on Twitter. In: Proceedings of the 7th Workshop on Geographic Information Retrieval, Orlando, pp 1–8

    Google Scholar 

  • Poseiro P, Reis M, Fortes C, Sabino A, Rodrigues A (2014a) Aplicação do sistema HIDRALERTA de previsões e alerta de inundações: caso de estudo da Costa da Caparica. In: Proceedings of the 3rd Jornadas de Engenharia Hidrográfica, Lisbon

    Google Scholar 

  • Poseiro P, Sabino A, Fortes CJ, Reis MT, Rodrigues A (2014b) Aplicação do sistema HIDRALERTA de previsão e alerta de inundações: Caso de estudo da Praia da Vitória. In: Proceedings of the 12th Congresso da Água, Number 1

    Google Scholar 

  • Son J, Kim A, Park S (2013) A location-based news article recommendation with explicit localized semantic analysis. In: Proceedings of the 36th International ACM SIGIR Conference on Research and Development in Information Retrieval, Dublin, pp 293–302

    Google Scholar 

  • Wang H, Terrovitis M, Mamoulis N (2013) Location recommendation in location-based social networks using user check-in data. In: Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Orlando

    Google Scholar 

  • Ye M, Yin P (2010) Location recommendation for location-based social networks. In: Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems, San Jose, Number c, pp 458–461

    Google Scholar 

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Sabino, A., Rodrigues, A. (2017). Productive Networks and Indirect Locations. In: Leitner, M., Jokar Arsanjani, J. (eds) Citizen Empowered Mapping. Geotechnologies and the Environment, vol 18. Springer, Cham. https://doi.org/10.1007/978-3-319-51629-5_5

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