A fuzzy approach to review-based recommendation: Design and optimization of a fuzzy classi cation scheme based on implicit features of textual reviews

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HASANZADEH S.; Fakhrahmad S. M.; TAHERI M.

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: Iranian Journal of Fuzzy Systems Year:2021 | Volume:18 | Issue:6 Page(s): 83-99

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Information Journal Paper

Title

A fuzzy approach to review-based recommendation: Design and optimization of a fuzzy classi cation scheme based on implicit features of textual reviews

Author(s)

HASANZADEH S. | Fakhrahmad S. M. | TAHERI M. | Issue Writer Certificate

Keywords

Recommender systemsQ2

review-basedQ2

fuzzy classicationQ2

rule weighting.Q2

Abstract

In the design of Recommender systems, it is believed that the set of reviews written by a user can somehow reveal his/her interests, and the content of an item can also be implied from its corresponding reviews. The present study attempts to model both the users and the items via extracting key information from the existing textual reviews. Based on this information, a fuzzy rule-based classi er is designed and tuned, which aims to predict whether a typical user will be interested in a typical item or not. For this purpose, the set of all reviews belonging to a user are mapped to a vector representing the user's interests. Similarly, the set of reviews written by di erent users over an item are merged and mapped to a vector representing the item. By conjoining these two vectors, a longer vector is obtained which will be used as the input of the classi er. To optimize the classi er, an adaptive approach is suggested and rule-weight learning is carried out, accordingly. The performance of the proposed fuzzy recommender system was evaluated on the Amazon dataset. Experimental results narrate from the promising classi cation ability of the proposed recommender system compared to state of the art.

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APA: Copy

HASANZADEH, S., Fakhrahmad, S. M., & TAHERI, M.. (2021). A fuzzy approach to review-based recommendation: Design and optimization of a fuzzy classi cation scheme based on implicit features of textual reviews. IRANIAN JOURNAL OF FUZZY SYSTEMS, 18(6 ), 83-99. SID. https://sid.ir/paper/413977/en

Vancouver: Copy

HASANZADEH S., Fakhrahmad S. M., TAHERI M.. A fuzzy approach to review-based recommendation: Design and optimization of a fuzzy classi cation scheme based on implicit features of textual reviews. IRANIAN JOURNAL OF FUZZY SYSTEMS[Internet]. 2021;18(6 ):83-99. Available from: https://sid.ir/paper/413977/en

IEEE: Copy

S. HASANZADEH, S. M. Fakhrahmad, and M. TAHERI, “A fuzzy approach to review-based recommendation: Design and optimization of a fuzzy classi cation scheme based on implicit features of textual reviews,” IRANIAN JOURNAL OF FUZZY SYSTEMS, vol. 18, no. 6 , pp. 83–99, 2021, [Online]. Available: https://sid.ir/paper/413977/en

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