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FFM-SVD: A Novel Approach for Personality-aware Recommender Systems

Widdeson, Kai; Hadžidedić, Sunčica

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Kai Widdeson


This paper addresses and evaluates approaches to incorporating personality data into a recommender system. Automatic personality recognition is enabled by the LIWC dictionary. Personality-aware pre-filtering techniques are developed and discussed, with the introduced non-targeted stratified personality sampling performing the best. A novel personality-aware model, FFM-SVD, is proposed and shown to outperform alternative models in prediction accuracy.


Widdeson, K., & Hadžidedić, S. (2023). FFM-SVD: A Novel Approach for Personality-aware Recommender Systems. .

Conference Name 2022 IEEE/ACS 19th International Conference on Computer Systems and Applications (AICCSA)
Conference Location Abu Dhabi, UAE
Start Date Dec 5, 2022
End Date Dec 7, 2022
Acceptance Date Sep 27, 2022
Online Publication Date Jan 20, 2023
Publication Date 2023-01
Deposit Date Oct 25, 2022
Publicly Available Date Jul 28, 2023
Publisher Institute of Electrical and Electronics Engineers
Pages 1-8
Additional Information 5-8 Dec. 2022


Accepted Conference Proceeding (519 Kb)

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