A Fuzzy-Based Discounts Recommender System for Public Tax Payment

  • Jaime Meza
  • Luis Terán
  • Martha Tomalá
Part of the Fuzzy Management Methods book series (FMM)


Governmental institutions around the world need funding to keep and raise their social and financial programs. One of the main incomes of different national and local governments is based on taxation. Increasing the income through tax payers has been and remains a challenge for government institutions. On the other hand, recommender systems (RSs) have presented evidence of successful results to improve business revenues in the field of eCommerce. This research presents a fuzzy-based recommender system model and its preliminary outcomes applied to a dataset from the Municipality of Quito to advise citizens on their payments behaviour. The proposed model shows some insights in the use of RSs to increase citizens’ awareness over tax payments and therefore enhance governmental institutions’ incomes. At the end of this chapter, preliminary results of the system developed are presented.



Authors would like to thank the members of Information System Research Group ( at the University of Fribourg for contributing with valuable thoughts and comments. We specially thank Prof. Dr. Andreas Meier for his support and collaboration.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Jaime Meza
    • 1
  • Luis Terán
    • 2
    • 3
  • Martha Tomalá
    • 4
  1. 1.Universidad Técnica de Manabí (UTM)PortoviejoEcuador
  2. 2.University of FribourgFribourgSwitzerland
  3. 3.Universidad de las Fuerzas Armadas ESPESangolquíEcuador
  4. 4.Municipality of District of Quito (MDMQ)QuitoEcuador

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