Review Article
A Survey of Long-Tail Item Recommendation Methods
Table 3
The summary on clustering-based long-tail item recommendation methods.
| | Ref. | Datasets | Evaluation metrics | Proposed methods |
| | [23] | MovieLens, BookCrossing | RMSE, MAE | AC (Adaptive Clustering) | | [24] | Amazon, Airbnb | PMI score (Point-Wise Mutual Information), precision, F1-score, diversity, novelty | EK-medoids (enhanced k-medoids algorithm), MaxEnt-BTM, TopicRec | | [29] | MovieLens, BookCrossing | RMSE, MAE | EI (Each Item), TC (Total Cluster), CT (Clustered Tail) | | [30] | e-commerce data (not public dataset) | NDCG | Based on AC and TC methods, the effects of three distance measurement methods are compared |
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