Combining usage and content in an online music recommendation system for music in the long-tail. - Marcos Aurélio Domingues; Fabien Gouyon; Alípio Mário Jorge; José Paulo Leal; João Vinagre; Luís Lemos; Mohamed Sordo (WWW (Companion Volume), 2012)

Forgetting mechanisms for scalable collaborative filtering. - João Vinagre; Alípio Mário Jorge (J. Braz. Comput. Soc., 2012)

Combining usage and content in an online recommendation system for music in the Long Tail. - Marcos Aurélio Domingues; Fabien Gouyon; Alípio Mário Jorge; José Paulo Leal; João Vinagre; Luís Lemos; Mohamed Sordo (Int. J. Multim. Inf. Retr., 2013)

Monitoring Recommender Systems: A Business Intelligence Approach. - Catarina Félix; Carlos Soares; Alípio Jorge; João Vinagre (ICCSA (6), 2014)

Fast Incremental Matrix Factorization for Recommendation with Positive-Only Feedback. - João Vinagre; Alípio Mário Jorge; João Gama 001 (UMAP, 2014)

Forgetting methods for incremental matrix factorization in recommender systems. - Pawel Matuszyk; João Vinagre; Myra Spiliopoulou; Alípio Mário Jorge; João Gama 001 (SAC, 2015)

Collaborative filtering with recency-based negative feedback. - João Vinagre; Alípio Mário Jorge; João Gama 001 (SAC, 2015)

Evaluation of recommender systems in streaming environments. - João Vinagre; Alípio Mário Jorge; João Gama 001 (CoRR, 2015)

An overview on the exploitation of time in collaborative filtering. - João Vinagre; Alípio Mário Jorge; João Gama 001 (WIREs Data Mining Knowl. Discov., 2015)

Scalable Online Top-N Recommender Systems. - Alípio M. Jorge; João Vinagre; Marcos Aurélio Domingues; João Gama 001; Carlos Soares; Pawel Matuszyk; Myra Spiliopoulou (EC-Web, 2016)

Online Bagging for Recommendation with Incremental Matrix Factorization. - João Vinagre; Alípio Mário Jorge; João Gama 001 (STREAMEVOLV@ECML-PKDD, 2016)

Data-Driven Relevance Judgments for Ranking Evaluation. - Nuno Moniz; Luís Torgo; João Vinagre (CoRR, 2016)

Scalable adaptive collaborative filtering - João Vinagre (2016)

Improving Incremental Recommenders with Online Bagging. - João Vinagre; Alípio Mário Jorge; João Gama 001 (EPIA, 2017)

Online Gradient Boosting for Incremental Recommender Systems. - João Vinagre; Alípio Mário Jorge; João Gama 001 (DS, 2018)

Self Hyper-parameter Tuning for Stream Recommendation Algorithms. - Bruno Veloso; João Gama 001; Benedita Malheiro; João Vinagre (DMLE/IOTSTREAMING@PKDD/ECML, 2018)

Incremental Matrix Co-factorization for Recommender Systems with Implicit Feedback. - Susan C. Anyosa; João Vinagre; Alípio M. Jorge (WWW (Companion Volume), 2018)

ORSUM Chairs' Welcome & Organization. - Alípio Jorge; João Vinagre; Pawel Matuszyk; Myra Spiliopoulou (WWW (Companion Volume), 2018)

Online bagging for recommender systems. - João Vinagre; Alípio Mário Jorge; João Gama 001 (Expert Syst. J. Knowl. Eng., 2018)

Forgetting techniques for stream-based matrix factorization in recommender systems. - Pawel Matuszyk; João Vinagre; Myra Spiliopoulou; Alípio Mário Jorge; João Gama 001 (Knowl. Inf. Syst., 2018)

Incremental Multi-Dimensional Recommender Systems: Co-Factorization vs Tensors. - Miguel Sozinho Ramalho; João Vinagre; Alípio Mário Jorge; Rafaela Bastos (ORSUM@RecSys, 2019)

ORSUM 2019 2nd workshop on online recommender systems and user modeling. - João Vinagre; Alípio Mário Jorge; Albert Bifet; Marie Al-Ghossein (RecSys, 2019)

ORSUM - Workshop on Online Recommender Systems and User Modeling. - João Vinagre; Alípio Mário Jorge; Marie Al-Ghossein; Albert Bifet (RecSys, 2020)

Partially Monotonic Learning for Neural Networks. - Joana Trindade; João Vinagre; Kelwin Fernandes; Nuno Paiva; Alípio Jorge (IDA, 2021)

ORSUM 2021 - 4th Workshop on Online Recommender Systems and User Modeling. - João Vinagre; Alípio Mário Jorge; Marie Al-Ghossein; Albert Bifet (RecSys, 2021)

AutoFITS: Automatic Feature Engineering for Irregular Time Series. - Pedro Costa; Vítor Cerqueira; João Vinagre (CoRR, 2021)

Hyperparameter self-tuning for data streams. - Bruno Veloso; João Gama 001; Benedita Malheiro; João Vinagre (Inf. Fusion, 2021)

A Hybrid Recommender System for Improving Automatic Playlist Continuation. - Anna Gatzioura; João Vinagre; Alípio Mário Jorge; Miquel Sànchez-Marrè (IEEE Trans. Knowl. Data Eng., 2021)

Statistically Robust Evaluation of Stream-Based Recommender Systems. - João Vinagre; Alípio Mário Jorge; Conceição Rocha; João Gama 001 (IEEE Trans. Knowl. Data Eng., 2021)

Flexible Fine-grained Data Access Management for Hyperledger Fabric. - João Parente; Ana Nunes Alonso; Fábio Coelho; João Vinagre; Paulo Bastos (BCCA, 2022)

Poster: User Sessions on Tor Onion Services: Can Colluding ISPs Deanonymize Them at Scale? - Daniela Lopes; Pedro Medeiros; Jin-Dong Dong; Diogo Barradas; Bernardo Portela; João Vinagre; Bernardo Ferreira; Nicolas Christin; Nuno Santos 001 (CCS, 2022)

Privacy-Preserving Machine Learning in Life Insurance Risk Prediction. - Klismam Pereira; João Vinagre; Ana Nunes Alonso; Fábio Coelho; Melânia Carvalho (PKDD/ECML Workshops (2), 2022)

ORSUM 2022 - 5th Workshop on Online Recommender Systems and User Modeling. - João Vinagre; Marie Al-Ghossein; Alípio Mário Jorge; Albert Bifet; Ladislav Peska (RecSys, 2022)

Proceedings of the 4th Workshop on Online Recommender Systems and User Modeling - ORSUM 2021. - João Vinagre; Alípio Mário Jorge; Marie Al-Ghossein; Albert Bifet (CoRR, 2022)

Federated Anomaly Detection over Distributed Data Streams. - Paula Raissa Silva; João Vinagre; João Gama 001 (CoRR, 2022)

Preface to the special issue on dynamic recommender systems and user models. - João Vinagre; Alípio Mário Jorge; Marie Al-Ghossein; Albert Bifet; Paolo Cremonesi (User Model. User Adapt. Interact., 2022)

Mining Causal Links Between TV Sports Content and Real-World Data. - Duarte Melo; Jessica C. Delmoral; João Vinagre (EPIA (1), 2023)

Hybrid SkipAwareRec: A Streaming Music Recommendation System. - Rui Ramos; Lino Oliveira; João Vinagre (EPIA (1), 2023)

Measuring Latency-Accuracy Trade-Offs in Convolutional Neural Networks. - André Tse; Lino Oliveira; João Vinagre (EPIA (1), 2023)

Fairness and Diversity in Information Access Systems. - Lorenzo Porcaro; Carlos Castillo 001; Emilia Gómez; João Vinagre (EWAF, 2023)

ORSUM 2023 - 6th Workshop on Online Recommender Systems and User Modeling. - João Vinagre; Marie Al-Ghossein; Ladislav Peska; Alípio Mário Jorge; Albert Bifet (RecSys, 2023)

A DTW Approach for Complex Data A Case Study with Network Data Streams. - Paula Raissa Silva; João Vinagre; João Gama 001 (SAC, 2023)

Behind Recommender Systems: the Geography of the ACM RecSys Community. - Lorenzo Porcaro; João Vinagre; Pedro Frau; Isabelle Hupont; Emilia Gómez (CoRR, 2023)

Towards federated learning: An overview of methods and applications. - Paula Raissa Silva; João Vinagre; João Gama 001 (WIREs Data. Mining. Knowl. Discov., 2023)

Federated Online Learning for Heavy Hitter Detection. - Paula Raissa Silva; João Vinagre; João Gama 001 (ECAI, 2024)

Flow Correlation Attacks on Tor Onion Service Sessions with Sliding Subset Sum. - Daniela Lopes; Jin-Dong Dong; Pedro Medeiros; Daniel Castro 004; Diogo Barradas; Bernardo Portela; João Vinagre; Bernardo Ferreira; Nicolas Christin; Nuno Santos 001 (NDSS, 2024)

Rethinking negative sampling in content-based news recommendation. - Miguel Ângelo Rebelo; João Vinagre; Ivo Pereira; Álvaro Figueira (CoRR, 2024)

Data Access under the EU Digital Services Act and its Impact on User Modelling Research. - Erasmo Purificato; Ludovico Boratto; João Vinagre (UMAP (Adjunct Publication), 2025)

Budget-constrained Collaborative Renewable Energy Forecasting Market. - Carla Gonçalves; Ricardo J. Bessa; Tiago Teixeira; João Vinagre (CoRR, 2025)

Can We Trust AI Benchmarks? An Interdisciplinary Review of Current Issues in AI Evaluation. - Maria Eriksson; Erasmo Purificato; Arman Noroozian; João Vinagre; Guillaume Chaslot; Emilia Gómez; David Fernández Llorca (CoRR, 2025)

Measuring the stability and plasticity of recommender systems. - Maria João Lavoura; Robert Jungnickel; João Vinagre (CoRR, 2025)

Generative AI and the Future of the Digital Commons: Five Open Questions and Knowledge Gaps. - Arman Noroozian; Lorena Aldana; Marta Arisi; Hadi Asghari; Renata Avila; Pietro Giovanni Bizzaro; Ramya Chandrasekhar; Cristian Consonni; Deborah De Angelis; Francesca De Chiara; Maria del Rio-Chanona; Mélanie Dulong de Rosnay; et al. (CoRR, 2025)