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Assisting Users in Decisions Using Fuzzy Ontologies: Application in the Wine Market

Author

Listed:
  • Juan Antonio Morente-Molinera

    (Andalusian Research Institute in Data Science and Computational Intelligence, University of Granada, 18010 Granada, Spain)

  • Francisco Javier Cabrerizo

    (Andalusian Research Institute in Data Science and Computational Intelligence, University of Granada, 18010 Granada, Spain)

  • Sergio Alonso

    (Andalusian Research Institute in Data Science and Computational Intelligence, University of Granada, 18010 Granada, Spain)

  • Ignacio Javier Pérez

    (Department of Computer Sciences and Engineering, University of Cadiz, 11003 Cadiz, Spain)

  • Enrique Herrera-Viedma

    (Andalusian Research Institute in Data Science and Computational Intelligence, University of Granada, 18010 Granada, Spain)

Abstract

Nowadays, wine has become a very popular item to purchase. There are a lot of brands and a lot of different types of wines that have different prices and characteristics. Since there is a lot of options, it is easy for buyers to feel lost among the high number of possibilities. Therefore, there is a need for computational tools that help buyers to decide which is the wine that better fits their necessities. In this article, a decision support system built over a fuzzy ontology has been designed for helping people to select a wine. Two different possible architecture implementation designs are presented. Furthermore, imprecise information is used to design a comfortable way of providing information to the system. Users can use this comfortable communication system to express their preferences and provide their opinion about the selected products. Moreover, mechanisms to carry out a constant update of the fuzzy ontology are exposed.

Suggested Citation

  • Juan Antonio Morente-Molinera & Francisco Javier Cabrerizo & Sergio Alonso & Ignacio Javier Pérez & Enrique Herrera-Viedma, 2020. "Assisting Users in Decisions Using Fuzzy Ontologies: Application in the Wine Market," Mathematics, MDPI, vol. 8(10), pages 1-18, October.
    • Handle: RePEc:gam:jmathe:v:8:y:2020:i:10:p:1724-:d:424477
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    References listed on IDEAS

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    1. Chandra Mouliswaran Subramanian & Aswani Kumar Cherukuri, 2019. "Fuzzy Role Based Access Control Design using Fuzzy Ontology," International Journal of Information Technology Project Management (IJITPM), IGI Global, vol. 10(4), pages 118-136, October.
    2. Emma Norris & Ailbhe N. Finnerty & Janna Hastings & Gillian Stokes & Susan Michie, 2019. "A scoping review of ontologies related to human behaviour change," Nature Human Behaviour, Nature, vol. 3(2), pages 164-172, February.
    3. Sara Sweidan & Hazem El-Bakry & Sahar F. Sabbeh, 2020. "Construction of Liver Fibrosis Diagnosis Ontology From Fuzzy Extended ER Modeling: Construction of FibrOnto From an EER Model," International Journal of Decision Support System Technology (IJDSST), IGI Global, vol. 12(1), pages 46-69, January.
    4. Sui-zhi Luo & Hong-yu Zhang & Jian-qiang Wang & Lin Li, 2019. "Group decision-making approach for evaluating the sustainability of constructed wetlands with probabilistic linguistic preference relations," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 70(12), pages 2039-2055, December.
    5. Liu, Bingsheng & Zhou, Qi & Ding, Ru-Xi & Palomares, Iván & Herrera, Francisco, 2019. "Large-scale group decision making model based on social network analysis: Trust relationship-based conflict detection and elimination," European Journal of Operational Research, Elsevier, vol. 275(2), pages 737-754.
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    Cited by:

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