Effective Context-Aware Recommendations Based on Context Weighting Using Genetic Algorithm and Alleviating Data Sparsity
Context-aware collaborative filtering (CACF) is an effective approach for adapting recommendations under users’ specific contextual situations and aims to improve predictive accuracy for Context-aware recommender systems (CARSs). Incorporating context in recommender systems (RSs) considering the equ...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2020-08-01
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| Series: | Applied Artificial Intelligence |
| Online Access: | http://dx.doi.org/10.1080/08839514.2020.1775011 |