A Novel Hybrid Item-Based Similarity Method to Mitigate the Effects of Data Sparsity in Multi-Criteria Collaborative Filtering
Data sparsity presents a significant challenge for Recommendation Systems, particularly in neighborhood-based approaches that rely on co-ratings to compute similarity. As co-ratings decrease, these methods often struggle to generate accurate recommendations. Addressing the persistent challenge of da...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10960304/ |
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