Citation

Ang, Jun Yuan and Haw, Su Cheng (2022) Comparative Analysis of Techniques Used in Book-based Recommender System. In: ICDTE 2021: 2021 5th International Conference on Digital Technology in Education, 15 - 17 Sep. 2021, Busan, Republic of Korea.

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Abstract

Recommender system has become a very important tool to accelerate businesses’ growth by recommending suitable products to customers. However, in general public, their basic knowledge regarding recommender system still needs to be improved. Besides, the understanding on types of recommender systems and which type of recommender system performed the best need to be studied more in depth. Hence, this paper aims to study the existing techniques in recommender systems and evaluate their accuracy on predicting an item's rating. The chosen techniques will be implemented in the prototype using Python. With the help of graphical user interface, the result can be visualized in better manner. The results obtained from this paper will be able to prove or deny existing theory made on the techniques. Besides, commercial company would be able to have an insight on which type of recommender system that should be implemented.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Recommender system, collaborative filtering, book domain, comparative analysis, Singular Value Decomposition (SVD)
Subjects:	Z Bibliography. Library Science. Information Resources > ZA3038-5190 Information resources (General)
Divisions:	Faculty of Computing and Informatics (FCI)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	22 Feb 2022 03:43
Last Modified:	22 Feb 2022 03:43
URII:	http://shdl.mmu.edu.my/id/eprint/9980

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