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Identifying Touristic Interest Using Big Data Techniques

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Advances in Artificial Intelligence, Software and Systems Engineering (AHFE 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 965))

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Abstract

The objective of this paper is to identify the most visited places through a sentiment analysis of the tweets posted by people who visited a specific region of a city. The analyzed data were related to preferences and opinions about tourist places. This paper outlines an architectural framework and a methodology to collect and analysis big data from twitter platform.

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Authors and Affiliations

  1. Departamento de Informática y Computación, Escuela Politécnica Nacional, Quito, Ecuador

    Maritzol Tenemaza, Loza-Aguirre Edison, Myriam Peñafiel & Zaldumbide Juan

  2. Laboratorio ETSI, Universidad Politécnica de Madrid, Madrid, Spain

    Maritzol Tenemaza, Myriam Peñafiel, Zaldumbide Juan, Angelica de Antonio & Jaíme Ramirez

Authors
  1. Maritzol Tenemaza
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  2. Loza-Aguirre Edison
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  3. Myriam Peñafiel
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  4. Zaldumbide Juan
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  5. Angelica de Antonio
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  6. Jaíme Ramirez
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Corresponding author

Correspondence to Maritzol Tenemaza .

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Editors and Affiliations

  1. Institute for Advanced Systems Engineering, University of Central Florida, Orlando, FL, USA

    Tareq Ahram

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Tenemaza, M., Edison, LA., Peñafiel, M., Juan, Z., de Antonio, A., Ramirez, J. (2020). Identifying Touristic Interest Using Big Data Techniques. In: Ahram, T. (eds) Advances in Artificial Intelligence, Software and Systems Engineering. AHFE 2019. Advances in Intelligent Systems and Computing, vol 965. Springer, Cham. https://doi.org/10.1007/978-3-030-20454-9_17

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  • DOI: https://doi.org/10.1007/978-3-030-20454-9_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-20453-2

  • Online ISBN: 978-3-030-20454-9

  • eBook Packages: EngineeringEngineering (R0)

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