The Limits of Graph Samplers for Training Inductive Recommender Systems
T.E. Jendal, M. Lissandrini, P. Dolog, K. Hose, "The Limits of Graph Samplers for Training Inductive Recommender Systems," in VLDB, 2025
Python, PyTorch, C#, Git, Docker, Linux, SPARQL, and SQL
T.E. Jendal, M. Lissandrini, P. Dolog, K. Hose, "The Limits of Graph Samplers for Training Inductive Recommender Systems," in VLDB, 2025
T.E. Jendal, M. Lissandrini, P. Dolog, K. Hose, "Handling new users and items: a comparative study of inductive recommenders," in Data Min. Knowl. Disc., 2025
T.E. Jendal, TH. Le, H.W. Lauw, M. Lissandrini, P. Dolog, K. Hose, "Hypergraphs with Attention on Reviews for Explainable Recommendation," in ECIR, 2024
R. Biswas, L.A. Kaffee, M. Cochez, S. Dumbrava, T.E. Jendal, et al.. "Knowledge graph embeddings: open challenges and opportunities," in TGDK, 2023
T. E. Jendal, M. Lissandrini, P. Dolog, and K. Hose, “GInRec: A gated architecture for inductive recommendation using knowledge graphs,” in KaRS, 2023.
A. H. Brams*, A. L. Jakobsen*, T. E. Jendal*, M. Lissandrini, P. Dolog, and K. Hose, “Mindreader: Recommendation over knowledge graph entities with explicit user ratings,” in CIKM, 2020 
 * Equal contribution