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2020 – today
- 2025
[j12]Simone Borg Bruun
, Christina Lioma, Maria Maistro:
Recommending Target Actions Outside Sessions in the Data-poor Insurance Domain. Trans. Recomm. Syst. 3(1): 2:1-2:24 (2025)- 2024
- [j11]Tetsuya Sakai, Sijie Tao, Nuo Chen, Yujing Li, Maria Maistro, Zhumin Chu, Nicola Ferro:
On the Ordering of Pooled Web Pages, Gold Assessments, and Bronze Assessments. ACM Trans. Inf. Syst. 42(1): 23:1-23:31 (2024) - [j10]Sebastian Bruch, Claudio Lucchese, Maria Maistro, Franco Maria Nardini:
Special Section on Efficiency in Neural Information Retrieval. ACM Trans. Inf. Syst. 42(5): 113:1-113:4 (2024) - [c44]Timo Breuer, Maria Maistro:
Toward Evaluating the Reproducibility of Information Retrieval Systems with Simulated Users. ACM-REP 2024 - [c43]Tianyi Hu, Maria Maistro, Daniel Hershcovich:
Bridging Cultures in the Kitchen: A Framework and Benchmark for Cross-Cultural Recipe Retrieval. EMNLP 2024: 1068-1080 - [c42]Joakim Edin, Maria Maistro, Lars Maaløe, Lasse Borgholt, Jakob D. Havtorn, Tuukka Ruotsalo:
An Unsupervised Approach to Achieve Supervised-Level Explainability in Healthcare Records. EMNLP 2024: 4869-4890 - [c41]Sara Marjanovic, Haeun Yu, Pepa Atanasova, Maria Maistro, Christina Lioma, Isabelle Augenstein:
DYNAMICQA: Tracing Internal Knowledge Conflicts in Language Models. EMNLP (Findings) 2024: 14346-14360 - [c40]Theresia Veronika Rampisela, Tuukka Ruotsalo, Maria Maistro, Christina Lioma:
Can We Trust Recommender System Fairness Evaluation? The Role of Fairness and Relevance. SIGIR 2024: 271-281 - [c39]Simone Borg Bruun, Krisztian Balog, Maria Maistro:
Dataset and Models for Item Recommendation Using Multi-Modal User Interactions. SIGIR 2024: 709-718 - [p1]Nicola Ferro, Maria Maistro:
Evaluation of IR Systems. Information Retrieval: Advanced Topics and Techniques 2024: 111-191 - [i19]Simone Borg Bruun, Christina Lioma, Maria Maistro:
Recommending Target Actions Outside Sessions in the Data-poor Insurance Domain. CoRR abs/2403.00368 (2024) - [i18]Simone Borg Bruun, Krisztian Balog, Maria Maistro:
Dataset and Models for Item Recommendation Using Multi-Modal User Interactions. CoRR abs/2405.04246 (2024) - [i17]Theresia Veronika Rampisela, Tuukka Ruotsalo, Maria Maistro, Christina Lioma:
Can We Trust Recommender System Fairness Evaluation? The Role of Fairness and Relevance. CoRR abs/2405.18276 (2024) - [i16]Joakim Edin, Maria Maistro, Lars Maaløe, Lasse Borgholt, Jakob D. Havtorn, Tuukka Ruotsalo:
An Unsupervised Approach to Achieve Supervised-Level Explainability in Healthcare Records. CoRR abs/2406.08958 (2024) - [i15]Sara Vera Marjanovic, Haeun Yu, Pepa Atanasova, Maria Maistro, Christina Lioma, Isabelle Augenstein:
From Internal Conflict to Contextual Adaptation of Language Models. CoRR abs/2407.17023 (2024) - [i14]Joakim Edin, Andreas Geert Motzfeldt, Casper L. Christensen, Tuukka Ruotsalo, Lars Maaløe, Maria Maistro:
Normalized AOPC: Fixing Misleading Faithfulness Metrics for Feature Attribution Explainability. CoRR abs/2408.08137 (2024) - 2023
- [j9]Maria Maistro, Timo Breuer, Philipp Schaer, Nicola Ferro:
An in-depth investigation on the behavior of measures to quantify reproducibility. Inf. Process. Manag. 60(3): 103332 (2023) - [j8]Christine Bauer, Ben Carterette, Nicola Ferro, Norbert Fuhr, Joeran Beel, Timo Breuer, Charles L. A. Clarke, Anita Crescenzi, Gianluca Demartini, Giorgio Maria Di Nunzio, Laura Dietz, Guglielmo Faggioli, Bruce Ferwerda, Maik Fröbe, Matthias Hagen, Allan Hanbury, Claudia Hauff, Dietmar Jannach, Noriko Kando, Evangelos Kanoulas, Bart P. Knijnenburg, Udo Kruschwitz, Meijie Li, Maria Maistro, Lien Michiels, Andrea Papenmeier, Martin Potthast, Paolo Rosso, Alan Said, Philipp Schaer, Christin Seifert, Damiano Spina, Benno Stein, Nava Tintarev, Julián Urbano, Henning Wachsmuth, Martijn C. Willemsen, Justin Zobel:
Report on the Dagstuhl Seminar on Frontiers of Information Access Experimentation for Research and Education. SIGIR Forum 57(1): 7:1-7:28 (2023) - [c38]Simone Borg Bruun, Kacper Kenji Lesniak, Mirko Biasini, Vittorio Carmignani, Panagiotis Filianos, Christina Lioma, Maria Maistro:
Graph-Based Recommendation for Sparse and Heterogeneous User Interactions. ECIR (1) 2023: 182-199 - [c37]Joakim Edin, Alexander Junge, Jakob D. Havtorn, Lasse Borgholt, Maria Maistro, Tuukka Ruotsalo, Lars Maaløe:
Automated Medical Coding on MIMIC-III and MIMIC-IV: A Critical Review and Replicability Study. SIGIR 2023: 2572-2582 - [c36]Sebastian Bruch, Joel Mackenzie, Maria Maistro, Franco Maria Nardini:
ReNeuIR at SIGIR 2023: The Second Workshop on Reaching Efficiency in Neural Information Retrieval. SIGIR 2023: 3456-3459 - [e6]Jaap Kamps, Lorraine Goeuriot, Fabio Crestani, Maria Maistro, Hideo Joho, Brian Davis, Cathal Gurrin, Udo Kruschwitz, Annalina Caputo:
Advances in Information Retrieval - 45th European Conference on Information Retrieval, ECIR 2023, Dublin, Ireland, April 2-6, 2023, Proceedings, Part I. Lecture Notes in Computer Science 13980, Springer 2023, ISBN 978-3-031-28243-0 [contents] - [e5]Jaap Kamps, Lorraine Goeuriot, Fabio Crestani, Maria Maistro, Hideo Joho, Brian Davis, Cathal Gurrin, Udo Kruschwitz, Annalina Caputo:
Advances in Information Retrieval - 45th European Conference on Information Retrieval, ECIR 2023, Dublin, Ireland, April 2-6, 2023, Proceedings, Part II. Lecture Notes in Computer Science 13981, Springer 2023, ISBN 978-3-031-28237-9 [contents] - [e4]Jaap Kamps, Lorraine Goeuriot, Fabio Crestani, Maria Maistro, Hideo Joho, Brian Davis, Cathal Gurrin, Udo Kruschwitz, Annalina Caputo:
Advances in Information Retrieval - 45th European Conference on Information Retrieval, ECIR 2023, Dublin, Ireland, April 2-6, 2023, Proceedings, Part III. Lecture Notes in Computer Science 13982, Springer 2023, ISBN 978-3-031-28240-9 [contents] - [i13]Simone Borg Bruun, Kacper Kenji Lesniak, Mirko Biasini, Vittorio Carmignani, Panagiotis Filianos, Christina Lioma, Maria Maistro:
Graph-based Recommendation for Sparse and Heterogeneous User Interactions. CoRR abs/2301.11009 (2023) - [i12]Joakim Edin, Alexander Junge, Jakob D. Havtorn, Lasse Borgholt, Maria Maistro, Tuukka Ruotsalo, Lars Maaløe:
Automated Medical Coding on MIMIC-III and MIMIC-IV: A Critical Review and Replicability Study. CoRR abs/2304.10909 (2023) - [i11]Theresia Veronika Rampisela, Maria Maistro, Tuukka Ruotsalo, Christina Lioma:
Evaluation Measures of Individual Item Fairness for Recommender Systems: A Critical Study. CoRR abs/2311.01013 (2023) - 2022
- [j7]Nazli Goharian, Faegheh Hasibi, Maria Maistro, Suzan Verberne:
Report on the SIGIR 2022 Session on Women in IR (WIR). SIGIR Forum 56(2): 10:1-10:2 (2022) - [j6]Reuben Moyo, Stanley Ndebvu, Michael Zimba, Martin Dybdal, Maria Maistro, Benjamin Balder Bach:
Report on the Malawi Data Science Bootcamp 2021. SIGKDD Explor. 24(1): 46-48 (2022) - [c35]Kacper Kenji Lesniak, Maria Maistro:
Crowdsourcing Controller - Utilizing Reliable Agents in a Multiplayer Game. CoG 2022: 64-71 - [c34]Simone Borg Bruun, Maria Maistro, Christina Lioma:
Learning Recommendations from User Actions in the Item-poor Insurance Domain. RecSys 2022: 113-123 - [d1]Maria Maistro, Timo Breuer, Philipp Schaer, Nicola Ferro:
An in-depth Investigation on the Behaviour of Measures to Quantify Reproducibility. Zenodo, 2022
- [i10]Timo Breuer, Nicola Ferro, Maria Maistro, Philipp Schaer:
repro_eval: A Python Interface to Reproducibility Measures of System-oriented IR Experiments. CoRR abs/2201.07599 (2022) - [i9]Tetsuya Sakai, Sijie Tao, Maria Maistro, Zhumin Chu, Yujing Li, Nuo Chen, Nicola Ferro, Junjie Wang, Ian Soboroff, Yiqun Liu:
Corrected Evaluation Results of the NTCIR WWW-2, WWW-3, and WWW-4 English Subtasks. CoRR abs/2210.10266 (2022) - [i8]Simone Borg Bruun, Maria Maistro, Christina Lioma:
Learning Recommendations from User Actions in the Item-poor Insurance Domain. CoRR abs/2211.15360 (2022) - [i7]Maria Maistro, Lucas Chaves Lima, Jakob Grue Simonsen, Christina Lioma:
Principled Multi-Aspect Evaluation Measures of Rankings. CoRR abs/2212.00492 (2022) - [i6]Mirko Biasini, Vittorio Carmignani, Nicola Ferro, Panagiotis Filianos, Maria Maistro, Giorgio Maria Di Nunzio:
FullBrain: a Social E-learning Platform. CoRR abs/2212.01387 (2022) - [i5]Kacper Kenji Lesniak, Maria Maistro:
Crowdsourcing Controller - Utilizing Reliable Agents in a Multiplayer Game. CoRR abs/2212.02256 (2022) - 2021
- [j5]K. Selçuk Candan, Guglielmo Faggioli, Nicola Ferro, Lorraine Goeuriot, Bogdan Ionescu, Alexis Joly, Birger Larsen, Maria Maistro, Henning Müller, Florina Piroi:
Report on the 12th conference and labs of the evaluation forum (CLEF 2021): experimental IR meets multilinguality, multimodality, and interaction. SIGIR Forum 55(2): 15:1-15:12 (2021) - [c33]Maria Maistro, Lucas Chaves Lima, Jakob Grue Simonsen, Christina Lioma:
Principled Multi-Aspect Evaluation Measures of Rankings. CIKM 2021: 1232-1242 - [c32]Dongsheng Wang, Casper Hansen, Lucas Chaves Lima, Christian Hansen, Maria Maistro, Jakob Grue Simonsen, Christina Lioma:
Multi-head Self-attention with Role-Guided Masks. ECIR (2) 2021: 432-439 - [c31]Timo Breuer, Nicola Ferro, Maria Maistro, Philipp Schaer:
repro_eval: A Python Interface to Reproducibility Measures of System-Oriented IR Experiments. ECIR (2) 2021: 481-486 - [c30]Mirko Biasini, Vittorio Carmignani, Nicola Ferro, Panagiotis Filianos, Maria Maistro, Giorgio Maria Di Nunzio:
FullBrain: a Social E-learning Platform. IRCDL 2021: 25-41 - [c29]Charles L. A. Clarke, Maria Maistro, Mark D. Smucker:
Overview of the TREC 2021 Health Misinformation Track. TREC 2021 - [e3]Guglielmo Faggioli, Nicola Ferro, Alexis Joly, Maria Maistro, Florina Piroi:
Proceedings of the Working Notes of CLEF 2021 - Conference and Labs of the Evaluation Forum, Bucharest, Romania, September 21st - to - 24th, 2021. CEUR Workshop Proceedings 2936, CEUR-WS.org 2021 [contents] - [e2]K. Selçuk Candan, Bogdan Ionescu, Lorraine Goeuriot, Birger Larsen, Henning Müller, Alexis Joly, Maria Maistro, Florina Piroi, Guglielmo Faggioli, Nicola Ferro:
Experimental IR Meets Multilinguality, Multimodality, and Interaction - 12th International Conference of the CLEF Association, CLEF 2021, Virtual Event, September 21-24, 2021, Proceedings. Lecture Notes in Computer Science 12880, Springer 2021, ISBN 978-3-030-85250-4 [contents] - [i4]Lucas Chaves Lima, Dustin Brandon Wright, Isabelle Augenstein, Maria Maistro:
University of Copenhagen Participation in TREC Health Misinformation Track 2020. CoRR abs/2103.02462 (2021) - 2020
- [j4]Nicola Ferro, Claudio Lucchese, Maria Maistro, Raffaele Perego:
Boosting learning to rank with user dynamics and continuation methods. Inf. Retr. J. 23(6): 528-554 (2020) - [c28]Nicola Ferro, Claudio Lucchese, Maria Maistro, Raffaele Perego:
Improving Learning to Rank By Leveraging User Dynamics and Continuation Methods. SEBD 2020: 210-217 - [c27]Timo Breuer, Nicola Ferro, Norbert Fuhr, Maria Maistro, Tetsuya Sakai, Philipp Schaer, Ian Soboroff:
How to Measure the Reproducibility of System-oriented IR Experiments. SIGIR 2020: 349-358 - [c26]Charles L. A. Clarke, Saira Rizvi, Mark D. Smucker, Maria Maistro, Guido Zuccon:
Overview of the TREC 2020 Health Misinformation Track. TREC 2020 - [c25]Lucas Chaves Lima, Dustin Brandon Wright, Isabelle Augenstein, Maria Maistro:
University of Copenhagen Participation in TREC Health Misinformation Track 2020. TREC 2020 - [i3]Timo Breuer, Nicola Ferro, Norbert Fuhr, Maria Maistro, Tetsuya Sakai, Philipp Schaer, Ian Soboroff:
How to Measure the Reproducibility of System-oriented IR Experiments. CoRR abs/2010.13447 (2020) - [i2]Lucas Chaves Lima, Casper Hansen, Christian Hansen, Dongsheng Wang, Maria Maistro, Birger Larsen, Jakob Grue Simonsen, Christina Lioma:
Denmark's Participation in the Search Engine TREC COVID-19 Challenge: Lessons Learned about Searching for Precise Biomedical Scientific Information on COVID-19. CoRR abs/2011.12684 (2020) - [i1]Dongsheng Wang, Casper Hansen, Lucas Chaves Lima, Christian Hansen, Maria Maistro, Jakob Grue Simonsen, Christina Lioma:
Multi-Head Self-Attention with Role-Guided Masks. CoRR abs/2012.12366 (2020)
2010 – 2019
- 2019
- [c24]Nicola Ferro, Norbert Fuhr, Maria Maistro, Tetsuya Sakai, Ian Soboroff:
CENTRE@CLEF2019: Overview of the Replicability and Reproducibility Tasks. CLEF (Working Notes) 2019 - [c23]Nicola Ferro, Norbert Fuhr, Maria Maistro, Tetsuya Sakai, Ian Soboroff:
Overview of CENTRE@CLEF 2019: Sequel in the Systematic Reproducibility Realm. CLEF 2019: 287-300 - [c22]Nicola Ferro, Norbert Fuhr, Maria Maistro, Tetsuya Sakai, Ian Soboroff:
CENTRE@CLEF 2019. ECIR (2) 2019: 283-290 - 2018
- [j3]Maria Maistro:
Exploiting User Signals and Stochastic Models to Improve Information Retrieval Systems and Evaluation. SIGIR Forum 52(2): 174-175 (2018) - [c21]Nicola Ferro, Claudio Lucchese, Maria Maistro, Raffaele Perego:
Continuation Methods and Curriculum Learning for Learning to Rank. CIKM 2018: 1523-1526 - [c20]Nicola Ferro, Maria Maistro, Tetsuya Sakai, Ian Soboroff:
CENTRE@CLEF2018: Overview of the Replicability Task. CLEF (Working Notes) 2018 - [c19]Nicola Ferro, Maria Maistro, Tetsuya Sakai, Ian Soboroff:
Overview of CENTRE@CLEF 2018: A First Tale in the Systematic Reproducibility Realm. CLEF 2018: 239-246 - [c18]Damiano Spina, Maria Maistro, Yongli Ren, Sargol Sadeghi, Wilson Wong, Timothy Baldwin, Lawrence Cavedon, Alistair Moffat, Mark Sanderson, Falk Scholer, Justin Zobel:
A Preliminary Comparison of Job, Talent, and Web Search. IIR 2018 - [c17]Maristella Agosti, Giorgio Maria Di Nunzio, Nicola Ferro, Maria Maistro, Stefano Marchesin, Nicola Orio, Chiara Ponchia, Gianmaria Silvello:
Thirty Years of Digital Libraries Research at the University of Padua: The User Side. IRCDL 2018: 42-54 - [c16]Marco Ferrante, Nicola Ferro, Maria Maistro:
How to Robustly Combine Judgements from Crowd Assessors with AWARE. SEBD 2018 - [c15]Giorgio Maria Di Nunzio, Maria Maistro, Federica Vezzani:
A Gamified Approach to Naïve Bayes Classification: A Case Study for Newswires and Systematic Medical Reviews. WWW (Companion Volume) 2018: 1139-1146 - 2017
- [j2]Nicola Ferro, Claudio Lucchese, Maria Maistro, Raffaele Perego:
Report on LEARNER 2017: 1st International Workshop on LEARning Next gEneration Rankers. SIGIR Forum 51(3): 145-151 (2017) - [j1]Marco Ferrante, Nicola Ferro, Maria Maistro:
AWARE: Exploiting Evaluation Measures to Combine Multiple Assessors. ACM Trans. Inf. Syst. 36(2): 20:1-20:38 (2017) - [c14]Nicola Ferro, Claudio Lucchese, Maria Maistro, Raffaele Perego:
LEARning Next gEneration Rankers (LEARNER 2017). ICTIR 2017: 331-332 - [c13]Giorgio Maria Di Nunzio, Maria Maistro, Daniel Zilio:
A Game of Lines: Developing Game Mechanics for Text Classification. IIR 2017: 40-47 - [c12]Nicola Ferro, Claudio Lucchese, Maria Maistro, Raffaele Perego:
On Including the User Dynamic in Learning to Rank. SIGIR 2017: 1041-1044 - [c11]Damiano Spina, Maria Maistro, Yongli Ren, Sargol Sadeghi, Wilson Wong, Timothy Baldwin, Lawrence Cavedon, Alistair Moffat, Mark Sanderson, Falk Scholer, Justin Zobel:
Understanding User Behavior in Job and Talent Search: An Initial Investigation. eCOM@SIGIR 2017 - [c10]Maria Maistro:
Adapting Information Retrieval to User Signals via Stochastic Models. WSDM 2017: 843 - [e1]Nicola Ferro, Claudio Lucchese, Maria Maistro, Raffaele Perego:
Proceedings of the 1st International Workshop on LEARning Next gEneration Rankers co-located with the 3rd ACM International Conference on the Theory of Information Retrieval (ICTIR 2017), Amsterdam, The Netherlands, October 1, 2017. CEUR Workshop Proceedings 2007, CEUR-WS.org 2017 [contents] - 2016
- [c9]Giorgio Maria Di Nunzio, Maria Maistro, Daniel Zilio:
Gamification for IR: The Query Aspects Game. CLiC-it/EVALITA 2016 - [c8]Nicola Ferro, Marco Ferrante, Maria Maistro:
Basis of a Formal Framework for Information Retrieval Evaluation Measurements. IIR 2016 - [c7]Giorgio Maria Di Nunzio, Maria Maistro, Daniel Zilio:
Gamification for Machine Learning: The Classification Game. GamifIR@SIGIR 2016: 45-52 - [c6]Giorgio Maria Di Nunzio, Maria Maistro, Daniel Zilio:
The University of Padua (IMS) at TREC 2016 Total Recall Track. TREC 2016 - 2015
- [c5]Maria Maistro:
Improving Information Retrieval Evaluation via Markovian User Models and Visual Analytics. FDIA 2015 - [c4]Marco Ferrante, Nicola Ferro, Maria Maistro:
Towards a Formal Framework for Utility-oriented Measurements of Retrieval Effectiveness. ICTIR 2015: 21-30 - [c3]Marco Ferrante, Nicola Ferro, Maria Maistro:
Markov Precision: Modelling User Behaviour over Rank and Time. IIR 2015 - 2014
- [c2]Marco Ferrante, Nicola Ferro, Maria Maistro:
Rethinking How to Extend Average Precision to Graded Relevance. CLEF 2014: 19-30 - [c1]Marco Ferrante, Nicola Ferro, Maria Maistro:
Injecting user models and time into precision via Markov chains. SIGIR 2014: 597-606
Coauthor Index
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