Online recommendation method of Malaysian medical tourism products based on collaborative filtering algorithm
Conventional online recommendation methods for medical tourism products mainly use the SVD (Singular Value Decomposition) matrix decomposition method to obtain the recommendation feature vector, which is vulnerable to the sparsity of the interaction matrix, resulting in poor online recommendation re...
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| Main Authors: | , |
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| Format: | Article |
| Language: | en |
| Published: |
Success Culture Press
2023
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| Online Access: | http://eprints.utem.edu.my/id/eprint/27365/2/0108724122023583.PDF http://eprints.utem.edu.my/id/eprint/27365/ https://www.aasmr.org/liss/Vol.10/No.2%202023/Vol.10%20No.2.6.pdf |
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| Summary: | Conventional online recommendation methods for medical tourism products mainly use the SVD (Singular Value Decomposition) matrix decomposition method to obtain the recommendation feature vector, which is vulnerable to the sparsity of the interaction matrix, resulting in poor online recommendation results. Therefore, it is necessary to design a new online recommendation method for Malaysian medical tourism products based on collaborative filtering algorithm. That is to say, the Malaysian medical tourism products are modularized, the subsequent user preference similarity calculation is carried out through effective user modeling, and the online recommendation of tourism products is realized by using the collaborative filtering algorithm. The experimental results show that the online recommendation method designed for Malaysian medical tourism products has a good recommendation effect, and the product hits of several different types of tourism products are high after recommendation, which proves that the online
recommendation method designed is reliable, has certain application value, and has made certain contributions to improving the comprehensive profits of tourism products. |
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