Supervisión remota en el entrenamiento de un clasificador de sentimientos en comentarios turísticos

  1. Martín, C. 1
  2. Aguilar, R.M. 1
  3. Torres, J.M. 1
  4. Díaz S. 1
  1. 1 Universidad de La Laguna
    info

    Universidad de La Laguna

    San Cristobal de La Laguna, España

    ROR https://ror.org/01r9z8p25

Liburua:
XXXIX Jornadas de Automática: actas. Badajoz, 5-7 de septiembre de 2018
  1. Inés Tejado Balsera (coord.)
  2. Emiliano Pérez Hernández (coord.)
  3. Antonio José Calderón Godoy (coord.)
  4. Isaías González Pérez (coord.)
  5. Pilar Merchán García (coord.)
  6. Jesús Lozano Rogado (coord.)
  7. Santiago Salamanca Miño (coord.)
  8. Blas M. Vinagre Jara (coord.)

Argitaletxea: Universidad de Extremadura

ISBN: 978-84-9749-756-5,  978-84-09-04460-3

Argitalpen urtea: 2018

Orrialdeak: 644-650

Biltzarra: Jornadas de Automática (39. 2018. Badajoz)

Mota: Biltzar ekarpena

DOI: 10.17979/SPUDC.9788497497565.0644 DIALNET GOOGLE SCHOLAR lock_openRUC editor

Laburpena

This paper describes an algorithm for automatically identifying the sentiments expressed by tourists on eWOM (Electronic Word of Mouth) platforms. Based on reviews published by tourists after staying in hotels, a classifier is trained using an LSTM (Long short-term memory supervised learning algorithm. The improvement of the training process with the use of remote supervision is demonstrated. The increase in the number of samples in the training set, although these present noise, improves the results of the classifier. We present a use case for this method involving a group of hotels located on the island of Tenerife (Canary Islands).

Datuen iturria: Dialnet