Papers with Explainable recommendation
Explainable Recommendation with Personalized Review Retrieval and Aspect Learning (2023.acl-long)
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| Challenge: | Recent years have witnessed a growing interest in the development of explainable recommendation models. |
| Approach: | They propose a model that combines prediction and generation tasks to produce more persuasive explanations by obtaining additional information from the training sets. |
| Outcome: | The proposed model outperforms state-of-the-art models on three datasets and shows that it is more persuasive than previous models. |
You May Like This Hotel Because ...: Identifying Evidence for Explainable Recommendations (2020.aacl-main)
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| Challenge: | Several studies have addressed explainable recommendations that produce natural language sentences . however, this task cannot explain detailed evidences for each hotel . |
| Approach: | They propose to decompose the process into two subtasks: Evidence Identification and Evidence Explanation. |
| Outcome: | The proposed model can explain evidences in recommending hotels given vague requests . it can find evidence sentences with respect to various vague requests and generate recommendation sentences . |
Incorporating Review-missing Interactions for Generative Explainable Recommendation (2025.coling-main)
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| Challenge: | Existing models of explainable recommendation use user reviews as ground truths, but in practice, a large amount of users may not leave reviews after purchasing items. |
| Approach: | They propose to incorporate user preferences into explainable recommender models by leveraging generative models to predict the missing reviews and then training the model based on all the predicted and original reviews. |
| Outcome: | The proposed model improves the explanation quality on three publicly available datasets. |