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A hybrid recommender system for an online store using a fuzzy expert system

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17310%2F23%3AA2402GNH" target="_blank" >RIV/61988987:17310/23:A2402GNH - isvavai.cz</a>

  • Result on the web

    <a href="https://www.sciencedirect.com/science/article/pii/S0957417422016293" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0957417422016293</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.eswa.2022.118565" target="_blank" >10.1016/j.eswa.2022.118565</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    A hybrid recommender system for an online store using a fuzzy expert system

  • Original language description

    Nowadays, various recommender systems are popular and their main aim is to recommend suitable content to the user based on various parameters. This article proposes a hybrid recommender system, Eshop recommender, which combines a recommender module composed of three subsystems (the subsystems use collaborative-filtering and content-based approaches) and a fuzzy expert system. It is an e-shopping recommender system for suggesting suitable products. The system works with different user preferences and their activity on the e-shop, and the resulting list of recommended products is created using the fuzzy expert system. The expert system works with several parameters - similarity level with already rated products, coefficient of purchased product, and an average rating of the product. Due to this, our proposed system achieves promising results based on standard metrics (Precision, Recall, F1-measure). The system achieves results above 90%. The system also achieves better results than traditional approaches. The main contribution is creating a comprehensive hybrid system in the area of product recommendation in an online store, which has been validated on a group of real users and compared with other traditional approaches and the recommendation module of another online store.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2023

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Expert Systems with Applications

  • ISSN

    0957-4174

  • e-ISSN

    1873-6793

  • Volume of the periodical

  • Issue of the periodical within the volume

    February 2023

  • Country of publishing house

    GB - UNITED KINGDOM

  • Number of pages

    16

  • Pages from-to

  • UT code for WoS article

    000870936600008

  • EID of the result in the Scopus database

    2-s2.0-85137594859