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Found 5 papers, 1 papers with code
Simple and Powerful Architecture for Inductive Recommendation Using Knowledge Graph Convolutions
In this work, we propose SimpleRec, a strong baseline that uses a graph neural network and a KG to provide better recommendations than related inductive methods for new users and items.
MindReader: Recommendation over Knowledge Graph Entities with Explicit User Ratings
As a demonstration of the importance of this new dataset, we present a comparative study of the effect of the inclusion of ratings on non-item KG entities in a variety of state-of-the-art recommendation models.
A Real-World Data Resource of Complex Sensitive Sentences Based on Documents from the Monsanto Trial
In this work we present a corpus for the evaluation of sensitive information detection approaches that addresses the need for real world sensitive information for empirical studies.
Improving Explainable Recommendations with Synthetic Reviews
We demonstrate that the synthetic personalised reviews have better recommendation performance than human written reviews.
Automatic Generation of Natural Language Explanations
The model generates text reviews given a combination of the review and ratings score that express opinions about different factors or aspects of an item.
