1 code implementation • European Conference on Information Retrieval 2024 • Juan Manuel Rodriguez, Nima Tavassoli, Eliezer Levy, Gil Lederman, Dima Sivov, Matteo Lissandrini, Davide Mottin
ConQA comprises 30 descriptive and 50 conceptual queries on 43k images with more than 100 manually annotated images per query.
Ranked #1 on Image Retrieval on ConQA Conceptual
no code implementations • 11 Aug 2023 • Jeff Z. Pan, Simon Razniewski, Jan-Christoph Kalo, Sneha Singhania, Jiaoyan Chen, Stefan Dietze, Hajira Jabeen, Janna Omeliyanenko, Wen Zhang, Matteo Lissandrini, Russa Biswas, Gerard de Melo, Angela Bonifati, Edlira Vakaj, Mauro Dragoni, Damien Graux
Large Language Models (LLMs) have taken Knowledge Representation -- and the world -- by storm.
no code implementations • 9 Sep 2022 • Theis E. Jendal, Matteo Lissandrini, Peter Dolog, Katja Hose
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.
1 code implementation • 8 Jun 2021 • Anders H. Brams, Anders L. Jakobsen, Theis E. Jendal, Matteo Lissandrini, Peter Dolog, Katja Hose
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.
no code implementations • 11 Mar 2021 • Georgia Troullinou, Haridimos Kondylakis, Matteo Lissandrini, Davide Mottin
Although popular in relational databases, view materialization for RDF and SPARQL has not yet transitioned into practice, due to the non-trivial application to the RDF graph model.
Knowledge Graphs Databases