Publications

  1. Abolghasemi, A., Askari, A., & Verberne, S. (2022). On the Interpolation of Contextualized Term-based Ranking with BM25 for Query-by-Example Retrieval. Proceedings of the The 8th ACM SIGIR International Conference on the Theory of Information Retrieval.
  2. Abolghasemi, A., Verberne, S., & Azzopardi, L. (2022). Improving BERT-based query-by-document retrieval with multi-task optimization. The 44th European Conference on Information Retrieval, 3–12. https://arxiv.org/abs/2202.00373
  3. Alexander, D., & de Vries, A. P. (2021). “This research is funded by ...”: Named Entity Recognition of Financial Information in Research Papers. BIR 2021: 11th International Workshop on Bibliometric-Enhanced Information Retrieval at ECIR 2021. http://ceur-ws.org/Vol-2847/paper-10.pdf
  4. Alexander, D., Kusa, W., & de Vries, A. P. (2022, May). ORCAS-I: Queries Annotated with Intent using Weak Supervision. SIGIR ’22: Proceedings of the 45rd International ACM SIGIR Conference on Research and Development in Information Retrieval. https://arxiv.org/abs/2205.00926
  5. Althammer, S. (2021). RUDI: Real-Time Learning to Update Dense Retrieval Indices. Proceedings of the Second International Conference on Design of Experimental Search & Information REtrieval Systems, Padova, Italy, September 15-18, 2021. http://ceur-ws.org/Vol-2950/paper-20.pdf
  6. Althammer, S., Askari, A., Verberne, S., & Hanbury, A. (2021). DoSSIER@COLIEE 2021: Leveraging dense retrieval and summarization-based re-ranking for case law retrieval. ArXiv Preprint ArXiv:2108.03937. https://arxiv.org/pdf/2108.03937.pdf
  7. Althammer, S., Buckley, M., Hofstätter, S., & Hanbury, A. (2021). Linguistically Informed Masking for Representation Learning in the Patent Domain. Proceedings of the 2nd Workshop on Patent Text Mining and Semantic Technologies (PatentSemTech) 2021 Co-Located with the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2021). https://arxiv.org/pdf/2106.05768.pdf
  8. Althammer, S., Hofstätter, S., & Hanbury, A. (2021). Cross-domain Retrieval in the Legal and Patent Domains: a Reproducibility Study. European Conference on Information Retrieval, 3–17. https://arxiv.org/abs/2012.11405
  9. Althammer, S., Hofstätter, S., Sertkan, M., Verberne, S., & Hanbury, A. (2022). Paragraph Aggregation Retrieval Model (PARM) for Dense Document-to-Document Retrieval. Advances in Information Retrieval, 44rd European Conference on IR Research, ECIR 2022. https://arxiv.org/abs/2201.01614
  10. Askari, A., & Verberne, S. (2021). Combining lexical and neural retrieval with longformer-based summarization for effective case law retrieval. Proceedings of the Second International Conference on Design of Experimental Search & Information Retrieval Systems, 162–170. https://raw.githubusercontent.com/arian-askari/arian-askari.github.io/main/papers/desires2021.pdf
  11. Askari, A., Verberne, S., & Pasi, G. (2022). Expert Finding in Legal Community Question Answering. European Conference on Information Retrieval, 22–30. https://arxiv.org/pdf/2201.07667.pdf
  12. Buckley, M., Althammer, S., & Qoku, A. (2021). PatentExplorer: Refining Patent Search with Domain-specific Topic Models. Proceedings of the 2nd Workshop on Patent Text Mining and Semantic Technologies (PatentSemTech) 2021 Co-Located with the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2021). http://ceur-ws.org/Vol-2909/paper7.pdf
  13. Espitia, Ó., & Pasi, G. (2021). Neural IR for Domain-Specific Tasks. Italian Information Retrieval (IIR) Workshop. https://ir.webis.de/anthology/2021.iir_workshop-2021.18/
  14. Feucht, M., Wu, Z., Althammer, S., & Tresp, V. (2021). Description-based Label Attention Classifier for Explainable ICD-9 Classification. Proceedings of the Seventh Workshop on Noisy User-Generated Text (W-NUT 2021), 62–66. https://doi.org/10.18653/v1/2021.wnut-1.8
  15. Ghafourian, Y. (2022). Relevance Models Based on the Knowledge Gap. European Conference on Information Retrieval (ECIR), 488–495. https://arxiv.org/pdf/2204.11568.pdf
  16. Ghafourian, Y., Knoth, P., & Hanbury, A. (2021). Information retrieval evaluation in knowledge acquisition tasks. Proceedings of the Third Workshop on Evaluation of Personalisation in Information Retrieval (WEPIR)@CHIIR, 88–95. http://oro.open.ac.uk/77160/1/paper-10.pdf
  17. Goeuriot, L., Suominen, H., Pasi, G., Bassani, E., Brew-Sam, N., González-Sáez, G., Kelly, L., Mulhem, P., Seneviratne, S., Gyanendra Upadhyay, R., & others. (2021). Consumer health search at CLEF eHealth 2021. CLEF 2021 Evaluation Labs and Workshop: Online Working Notes. CEUR-WS. http://ceur-ws.org/Vol-2936/paper-62.pdf
  18. Hofstätter, S., Althammer, S., Schröder, M., Sertkan, M., & Hanbury, A. (2020). Improving Efficient Neural Ranking Models with Cross-Architecture Knowledge Distillation. https://doi.org/10.48550/ARXIV.2010.02666
  19. Hofstätter, S., Althammer, S., Sertkan, M., & Hanbury, A. (2022a). Establishing Strong Baselines for TripClick Health Retrieval. Advances in Information Retrieval, 44rd European Conference on IR Research, ECIR 2022. https://arxiv.org/abs/2201.00365
  20. Hofstätter, S., Althammer, S., Sertkan, M., & Hanbury, A. (2022b). A Time-Optimized Content Creation Workflow for Remote Teaching. Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V. 1, 731–737. https://arxiv.org/abs/2110.05601
  21. Hofstätter, S., Khattab, O., Althammer, S., Sertkan, M., & Hanbury, A. (2022). Introducing Neural Bag of Whole-Words with ColBERTer: Contextualized Late Interactions using Enhanced Reduction. https://doi.org/10.48550/ARXIV.2203.13088
  22. Hofstätter, S., Lipani, A., Althammer, S., Zlabinger, M., & Hanbury, A. (2021). Mitigating the Position Bias of Transformer Models in Passage Re-Ranking. Advances in Information Retrieval, 43rd European Conference on IR Research, ECIR 2021. https://arxiv.org/abs/2101.06980
  23. Kamateri, E., Stamatis, V., Diamantaras, K., & Salampasis, M. (2022). Automated Single-Label Patent Classification using Ensemble Classifiers. 14th International Conference on Machine Learning and Computing (ICMLC 2022). https://arxiv.org/pdf/2203.03552.pdf
  24. Kusa, W., & Ghafourian, Y. (2021). DOSSIER at TREC 2021 Clinical Trials Track. Text REtrieval Conferences (TREC). https://trec.nist.gov/pubs/trec30/papers/DOSSIER-CT.pdf
  25. Kusa, W., Hanbury, A., & Knoth, P. (2022). Automation of Citation Screening for Systematic Literature Reviews Using Neural Networks: A Replicability Study. Advances in Information Retrieval, 584–598. https://arxiv.org/abs/2201.07534
  26. McGregor, M., Azzopardi, L., & Halvey, M. (2021). Untangling Cost, Effort, and Load in Information Seeking and Retrieval. Proceedings of the 2021 Conference on Human Information Interaction and Retrieval, 151–161. https://doi.org/10.1145/3406522.3446026
  27. Peikos, G., Espitia, O., & Pasi, G. (2021). UNIMIB at TREC 2021 Clinical Trials Track. Text REtrieval Conferences (TREC). https://trec.nist.gov/pubs/trec30/papers/UNIMIB-CT.pdf
  28. Peikos, G., & Pasi, G. (2021). Multidimensional Relevance in Legal and Health Domains. Italian Information Retrieval (IIR) Workshop. http://ceur-ws.org/Vol-2947/paper29.pdf
  29. Soufan, A., Ruthven, I., & Azzopardi, L. (2022). Searching the literature: an analysis of an exploratory search task. ACM SIGIR Conference on Human Information Interaction and Retrieval, 146–157. https://strathprints.strath.ac.uk/79229/1/Soufan_etal_CHIIR_2022_Searching_the_literature_an_analysis_of_an_exploratory_search_task.pdf
  30. Soufan, A., Ruthven, I., & Azzopardi, L. (2021). Untangling the concept of task in information seeking and retrieval. Proceedings of the 2021 ACM SIGIR International Conference on Theory of Information Retrieval, 73–81. https://strathprints.strath.ac.uk/76919/1/Soufan_etal_SIGIR_2021_Untangling_the_concept_of_task_in_information_seeking_and_retrieval.pdf
  31. Stamatis, V. (2022). End to End Neural Retrieval for Patent Prior Art Search. In: Et al. Advances in Information Retrieval. ECIR 2022. Lecture Notes in Computer Science,. https://link.springer.com/chapter/10.1007/978-3-030-99739-7_66
  32. Stamatis, V., & Salampasis, M. (2020). Results Merging in the Patent Domain. 24th Pan-Hellenic Conference on Informatics. https://dl.acm.org/doi/10.1145/3437120.3437313
  33. Stamatis, V., Salampasis, M., & Diamantaras, K. (2022). Machine Learning Methods for Results Merging in Patent Retrieval. Data Technologies and Applications. https://dl.acm.org/doi/fullHtml/10.1145/3437120.3437313
  34. Upadhyay, R., Pasi, G., & Viviani, M. (2021a). An Overview on Evaluation Labs and Open Issues in Health-related Credible Information Retrieval. Italian Information Retrieval (IIR) Workshop. http://ceur-ws.org/Vol-2947/paper31.pdf
  35. Upadhyay, R., Pasi, G., & Viviani, M. (2021b). Health Misinformation Detection in Web Content: A Structural-, Content-based, and Context-aware Approach based on Web2Vec. Proceedings of the Conference on Information Technology for Social Good, 19–24. https://dl.acm.org/doi/10.1145/3462203.3475898

This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 860721