6 citations · 8 across the 2 of their papers we have counts for
4 papers
Recommendations for Item Set Completion: On the Semantics of Item Co-Occurrence With Data Sparsity, Input Size, and Input Modalities
Iacopo Vagliano, Lukas Galke, Ansgar Scherp
We address the problem of recommending relevant items to a user in order to "complete" a partial set of items already known. We consider the two scenarios of citation and subject l…
Multi-Modal Adversarial Autoencoders for Recommendations of Citations and Subject Labels
Lukas Galke, Florian Mai, Iacopo Vagliano +1
We present multi-modal adversarial autoencoders for recommendation and evaluate them on two different tasks: citation recommendation and subject label recommendation. We analyze th…
Can Graph Neural Networks Go "Online"? An Analysis of Pretraining and Inference
Lukas Galke, Iacopo Vagliano, Ansgar Scherp
Large-scale graph data in real-world applications is often not static but dynamic, i. e., new nodes and edges appear over time. Current graph convolution approaches are promising,…
Content Recommendation through Semantic Annotation of User Reviews and Linked Data - An Extended Technical Report
Iacopo Vagliano, Diego Monti, Ansgar Scherp +1
Nowadays, most recommender systems exploit user-provided ratings to infer their preferences. However, the growing popularity of social and e-commerce websites has encouraged users…