Explainable Recommendation
29 papers with code • 2 benchmarks • 2 datasets
MovieLens
Tripadvisor Restaurant Reviews
Most implemented papers
Reinforcement Recommendation Reasoning through Knowledge Graphs for Explanation Path Quality
giacoballoccu/rep-path-reasoning-recsys
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However, the existing explainable recommendation approaches based on KG merely optimize the selected reasoning paths for product relevance, without considering any user-level property of the paths for explanation.
UCEpic: Unifying Aspect Planning and Lexical Constraints for Generating Explanations in Recommendation
Then, to obtain personalized explanations under this framework of insertion-based generation, we design a method of incorporating aspect planning and personalized references into the insertion process.
Question-Attentive Review-Level Recommendation Explanation
PreferredAI/QuestER
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IEEE International Conference on Big Data (Big Data) 2022
The form of explanation of interest here is presenting an existing review of the recommended item.
Uncovering ChatGPT's Capabilities in Recommender Systems
The debut of ChatGPT has recently attracted the attention of the natural language processing (NLP) community and beyond.
Towards Explainable Conversational Recommender Systems
To achieve this, we conduct manual and automatic approaches to extend these dialogues and construct a new CRS dataset, namely Explainable Recommendation Dialogues (E-ReDial).
Topic-Centric Explanations for News Recommendation
News recommender systems (NRS) have been widely applied for online news websites to help users find relevant articles based on their interests.
Sustainable Transparency in Recommender Systems: Bayesian Ranking of Images for Explainability
kominaru/brie
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Recommender Systems have become crucial in the modern world, commonly guiding users towards relevant content or products, and having a large influence over the decisions of users and citizens.
Finding Paths for Explainable MOOC Recommendation: A Learner Perspective
In this work, we propose an explainable recommendation system for MOOCs that uses graph reasoning.
Unlocking the Potential of Large Language Models for Explainable Recommendations
godfire66666/llm_rec_explanation
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In this study, we propose LLMXRec, a simple yet effective two-stage explainable recommendation framework aimed at further boosting the explanation quality by employing LLMs.
