Special Issue "Fuzzy Logic in Recommender Systems"

A special issue of Axioms (ISSN 2075-1680). This special issue belongs to the section "Logic".

Deadline for manuscript submissions: 20 April 2023 | Viewed by 590

Special Issue Editors

1. Human-IST Institute, University of Fribourg, Boulevard de Pérolles 90, Fribourg, Switzerland
2. School of Business, University of Applied Sciences and Arts, 6002 Lucerne, Switzerland
Interests: data science; digitalization; information systems; machine learning; explainable artificial intelligence; recommender systems; human-centered computing; e-business; e-government; e-participation; e-democracy; e-health; fuzzy classification
Special Issues, Collections and Topics in MDPI journals
Institute of Communication and Marketing, Lucerne University of Applied Sciences and Arts, Zentralstrasse 9, 6002 Lucerne, Switzerland
Interests: data science; machine learning; recommender systems; natural language processing; graph representation learning

Special Issue Information

Dear Colleagues,

We have the intention of launching a Special Issue in Axioms. The central topic in the Special Issue will be “Fuzzy Set Theory in Recommender Systems”. With today’s information overload, it has become increasingly difficult to analyze the huge amounts of data available and to generate appropriate management decisions. Furthermore, the data are often imprecise and will include both quantitative and qualitative elements. For these reasons, it is important to extend traditional decision-making processes by adding intuitive reasoning, human subjectivity, and imprecision.

In the age of Big Data, decision-making processes for economy and society must deal with uncertainty, vagueness, and imprecision. Therefore, the application of fuzzy sets and fuzzy logic for recommender systems becomes a hot topic.

Dr. Luis Terán
Dr. Guang Lu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Axioms is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.


  • ethical recommender systems for society
  • small data and GDPR-compliant recommender systems
  • human-centered recommender systems
  • socially and context-aware recommender systems
  • applications of fuzzy logic in recommender systems for different business domains
  • generalized framework for the application of fuzzy logic in recommender systems
  • new data sets suitable for the application of fuzzy logic in recommender systems
  • application of fuzzy logic in group recommendations
  • fuzzy logic approaches with natural language processing for recommendations
  • fuzzy logic approaches with (knowledge) graph representation learning for recommendations
  • fuzzy logic approaches in conversational recommender systems
  • fuzzy logic approaches with social network analysis in recommender systems
  • fuzzy-logic-based explainable recommender systems
  • trust and fuzzy-logic-based recommender systems

Published Papers

This special issue is now open for submission.
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