no code implementations • 1 Mar 2024 • Simone Borg Bruun, Christina Lioma, Maria Maistro
Our models cope with data scarcity by learning from multiple sessions and different types of user actions.
1 code implementation • 2 Nov 2023 • Theresia Veronika Rampisela, Maria Maistro, Tuukka Ruotsalo, Christina Lioma
To our knowledge, this is the first critical comparison of individual item fairness measures in recommender systems.
1 code implementation • 21 Apr 2023 • Joakim Edin, Alexander Junge, Jakob D. Havtorn, Lasse Borgholt, Maria Maistro, Tuukka Ruotsalo, Lars Maaløe
Medical coding is the task of assigning medical codes to clinical free-text documentation.
Ranked #1 on Medical Code Prediction on MIMIC-IV ICD-10
1 code implementation • 26 Jan 2023 • Simone Borg Bruun, Kacper Kenji Lesniak, Mirko Biasini, Vittorio Carmignani, Panagiotis Filianos, Christina Lioma, Maria Maistro
We propose a graph-based recommender model which utilizes heterogeneous interactions between users and content of different types and is able to operate well on small-scale datasets.
1 code implementation • 1 Dec 2022 • Maria Maistro, Lucas Chaves Lima, Jakob Grue Simonsen, Christina Lioma
Information Retrieval evaluation has traditionally focused on defining principled ways of assessing the relevance of a ranked list of documents with respect to a query.
1 code implementation • 28 Nov 2022 • Simone Borg Bruun, Maria Maistro, Christina Lioma
To address this, we present a recurrent neural network recommendation model that uses past user sessions as signals for learning recommendations.
no code implementations • 19 Oct 2022 • Tetsuya Sakai, Sijie Tao, Maria Maistro, Zhumin Chu, Yujing Li, Nuo Chen, Nicola Ferro, Junjie Wang, Ian Soboroff, Yiqun Liu
The noise is due to a fatal bug in the backend of our relevance assessment interface.
1 code implementation • 19 Jan 2022 • Timo Breuer, Nicola Ferro, Maria Maistro, Philipp Schaer
In this work we introduce repro_eval - a tool for reactive reproducibility studies of system-oriented information retrieval (IR) experiments.
no code implementations • 3 Mar 2021 • Lucas Chaves Lima, Dustin Brandon Wright, Isabelle Augenstein, Maria Maistro
Our approach consists of 3 steps: (1) we create an initial run with BM25 and RM3; (2) we estimate credibility and misinformation scores for the documents in the initial run; (3) we merge the relevance, credibility and misinformation scores to re-rank documents in the initial run.
1 code implementation • 22 Dec 2020 • Dongsheng Wang, Casper Hansen, Lucas Chaves Lima, Christian Hansen, Maria Maistro, Jakob Grue Simonsen, Christina Lioma
The state of the art in learning meaningful semantic representations of words is the Transformer model and its attention mechanisms.
no code implementations • 25 Nov 2020 • Lucas Chaves Lima, Casper Hansen, Christian Hansen, Dongsheng Wang, Maria Maistro, Birger Larsen, Jakob Grue Simonsen, Christina Lioma
This report describes the participation of two Danish universities, University of Copenhagen and Aalborg University, in the international search engine competition on COVID-19 (the 2020 TREC-COVID Challenge) organised by the U. S. National Institute of Standards and Technology (NIST) and its Text Retrieval Conference (TREC) division.
1 code implementation • 26 Oct 2020 • Timo Breuer, Nicola Ferro, Norbert Fuhr, Maria Maistro, Tetsuya Sakai, Philipp Schaer, Ian Soboroff
Replicability and reproducibility of experimental results are primary concerns in all the areas of science and IR is not an exception.