Word Sequential Using Deep LSTM And Matrix Factorization To Handle Rating Sparse Data For E-Commerce Recommender System
Recommender systems are essential engines to deliver product recommendations for e-commerce businesses. Successful adoption of recommender systems could significantly influence the growth of marketing targets. Collaborative filtering is a type of recommender system model that uses customers' ac...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi Limited
2021
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| Online Access: | http://eprints.utem.edu.my/id/eprint/25705/2/HANAFIBURHANWORD%20SEQUENTIAL%20USING%20DEEP%20LSTM.PDF http://eprints.utem.edu.my/id/eprint/25705/ https://downloads.hindawi.com/journals/cin/2021/8751173.pdf |
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