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Comparison <t>of</t> <t>RLRanker-PPO</t> with traditional ranking methods on Amazon and Kaggle datasets—(a) <t>CTR,</t> (b) Hit Rate@10, (c) NDCG@10, and (d) Engagement Score.
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Comparison of RLRanker-PPO with traditional ranking methods on Amazon and Kaggle datasets—(a) CTR, (b) Hit Rate@10, (c) NDCG@10, and (d) Engagement Score.

Journal: Scientific Reports

Article Title: DeepSentRec: a deep learning-based sentiment-aware product recommendation system

doi: 10.1038/s41598-026-45953-9

Figure Lengend Snippet: Comparison of RLRanker-PPO with traditional ranking methods on Amazon and Kaggle datasets—(a) CTR, (b) Hit Rate@10, (c) NDCG@10, and (d) Engagement Score.

Article Snippet: Figure (a) depicts the Click-Through Rate (CTR), where RLRanker-PPO exceeds the baselines by a large margin of 24.96% on Amazon and 23.41% on Kaggle.

Techniques: Comparison