An exploratory study of hierarchical fuzzy systems approach in a recommendation system / Tajul Rosli Razak ... [et al.]

Razak, Tajul Rosli and Abd Halim, Iman Hazwam and Jamaludin, Muhammad Nabil Fikri and Ismail, Mohammad Hafiz and Mohd Fauzi, Shukor Sanim (2019) An exploratory study of hierarchical fuzzy systems approach in a recommendation system / Tajul Rosli Razak ... [et al.]. Jurnal Intelek, 14 (2). pp. 174-186. ISSN 2231-7716


Recommendation system, also known as a recommender system, is a tool to help the user in providing a suggestion of a specific dilemma. Recently, the interest in developing a recommendation system in many fields has increased. Fuzzy Logic system (FLSs) is one of the approaches that can be used to model the recommendation systems as it can deal with uncertainty and imprecise information. However, one of the fundamental issues in FLS is the problem of the curse of dimensionality. That is, the number of rules in FLSs is increasing exponentially with the number of input variables. One effective way to overcome this problem is by using Hierarchical Fuzzy System (HFSs). This paper aims to explore the use of HFSs for Recommendation system. Specifically, we are interested in exploring and comparing the HFS and FLS for the Career path recommendation system (CPRS) based on four key criteria, namely topology, the number of rules, the rules structures and interpretability. The findings suggested that the HFS has advantages over FLS towards improving the interpretability models, in the context of a recommendation system example. This study contributes to providing an insight into the development of interpretable HFSs in the Recommendation systems.


Item Type: Article
Email / ID Num.
Razak, Tajul Rosli
Abd Halim, Iman Hazwam
Jamaludin, Muhammad Nabil Fikri
Ismail, Mohammad Hafiz
Mohd Fauzi, Shukor Sanim
Subjects: Q Science > QA Mathematics > Instruments and machines > Electronic Computers. Computer Science > System design
Q Science > QA Mathematics > Fuzzy logic
Divisions: Universiti Teknologi MARA, Perlis > Arau Campus
Journal or Publication Title: Jurnal Intelek
UiTM Journal Collections: UiTM Journal > Jurnal Intelek (JI)
ISSN: 2231-7716
Volume: 14
Number: 2
Page Range: pp. 174-186
Keywords: Fuzzy Logic Systems, Hierarchical Fuzzy Systems, Recommendation Systems
Date: December 2019
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