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ORCIDGuido Zuccon
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- affiliation: University of Queensland, Australia
- affiliation: Queensland University of Technology
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2020 – today
- 2023
[j25]Mohamed A. Sharaf
, Rischan Mafrur, Guido Zuccon:
Efficient Diversification for Recommending Aggregate Data Visualizations. IEEE Access 11: 62261-62280 (2023)- [j24]Hang Li, Ahmed Mourad, Shengyao Zhuang, Bevan Koopman, Guido Zuccon:
Pseudo Relevance Feedback with Deep Language Models and Dense Retrievers: Successes and Pitfalls. ACM Trans. Inf. Syst. 41(3): 62:1-62:40 (2023) - [j23]Xue Li, Catherine Zou, Robert Boots, Sen Wang, Weitong Chen, Guido Zuccon:
Artificial Intelligence in Evidence-based Medicine: Challenges and Opportunities. World Sci. Annu. Rev. Artif. Intell. 1: 2330002:1-2330002:19 (2023) - [c190]Ekaterina Khramtsova, Guido Zuccon, Xi Wang, Mahsa Baktashmotlagh:
Convolutional Persistence as a Remedy to Neural Model Analysis. AISTATS 2023: 10839-10855 - [c189]Sebastian Cross, Guido Zuccon, Ahmed Mourad:
A Reproducibility Study of Question Retrieval for Clarifying Questions. ECIR (3) 2023: 35-50 - [c188]Wojciech Kusa, Guido Zuccon, Petr Knoth, Allan Hanbury:
Outcome-based Evaluation of Systematic Review Automation. ICTIR 2023: 125-133 - [c187]Joel Mackenzie, Shengyao Zhuang, Guido Zuccon:
Exploring the Representation Power of SPLADE Models. ICTIR 2023: 143-147 - [c186]Shuyi Wang, Guido Zuccon:
An Analysis of Untargeted Poisoning Attack and Defense Methods for Federated Online Learning to Rank Systems. ICTIR 2023: 215-224 - [c185]Guido Zuccon, Harrisen Scells, Shengyao Zhuang:
Beyond CO2 Emissions: The Overlooked Impact of Water Consumption of Information Retrieval Models. ICTIR 2023: 283-289 - [c184]Shuai Wang, Harrisen Scells, Bevan Koopman, Guido Zuccon:
Can ChatGPT Write a Good Boolean Query for Systematic Review Literature Search? SIGIR 2023: 1426-1436 - [c183]Shengyao Zhuang, Linjun Shou, Guido Zuccon:
Augmenting Passage Representations with Query Generation for Enhanced Cross-Lingual Dense Retrieval. SIGIR 2023: 1827-1832 - [c182]Shuai Wang, Guido Zuccon:
Balanced Topic Aware Sampling for Effective Dense Retriever: A Reproducibility Study. SIGIR 2023: 2542-2551 - [c181]Bing Liu, Tiancheng Lan, Wen Hua, Guido Zuccon:
Dependency-aware Self-training for Entity Alignment. WSDM 2023: 796-804 - [c180]Hang Li, Bevan Koopman, Ahmed Mourad, Guido Zuccon:
AgAsk: A Conversational Search Agent for Answering Agricultural Questions. WSDM 2023: 1140-1143 - [c179]Shuai Wang, Hang Li, Guido Zuccon:
MeSH Suggester: A Library and System for MeSH Term Suggestion for Systematic Review Boolean Query Construction. WSDM 2023: 1176-1179 - [i37]Shuai Wang, Harrisen Scells, Bevan Koopman, Guido Zuccon:
Can ChatGPT Write a Good Boolean Query for Systematic Review Literature Search? CoRR abs/2302.03495 (2023) - [i36]Guido Zuccon, Bevan Koopman:
Dr ChatGPT, tell me what I want to hear: How prompt knowledge impacts health answer correctness. CoRR abs/2302.13793 (2023) - [i35]Shengyao Zhuang, Linjun Shou, Jian Pei, Ming Gong, Houxing Ren, Guido Zuccon, Daxin Jiang:
Typos-aware Bottlenecked Pre-Training for Robust Dense Retrieval. CoRR abs/2304.08138 (2023) - [i34]Shengyao Zhuang, Linjun Shou, Guido Zuccon:
Augmenting Passage Representations with Query Generation for Enhanced Cross-Lingual Dense Retrieval. CoRR abs/2305.03950 (2023) - [i33]Guido Zuccon, Harrisen Scells, Shengyao Zhuang:
Beyond CO2 Emissions: The Overlooked Impact of Water Consumption of Information Retrieval Models. CoRR abs/2306.16668 (2023) - [i32]Joel Mackenzie, Shengyao Zhuang, Guido Zuccon:
Exploring the Representation Power of SPLADE Models. CoRR abs/2306.16680 (2023) - [i31]Wojciech Kusa, Guido Zuccon, Petr Knoth, Allan Hanbury:
Outcome-based Evaluation of Systematic Review Automation. CoRR abs/2306.17614 (2023) - [i30]Shuyi Wang, Guido Zuccon:
An Analysis of Untargeted Poisoning Attack and Defense Methods for Federated Online Learning to Rank Systems. CoRR abs/2307.01565 (2023) - [i29]Shuai Wang, Harrisen Scells, Martin Potthast, Bevan Koopman, Guido Zuccon:
Generating Natural Language Queries for More Effective Systematic Review Screening Prioritisation. CoRR abs/2309.05238 (2023) - [i28]Sophia Althammer, Guido Zuccon, Sebastian Hofstätter, Suzan Verberne, Allan Hanbury:
Annotating Data for Fine-Tuning a Neural Ranker? Current Active Learning Strategies are not Better than Random Selection. CoRR abs/2309.06131 (2023) - 2022
- [j22]Shengyao Zhuang, Zhihao Qiao, Guido Zuccon:
Reinforcement online learning to rank with unbiased reward shaping. Inf. Retr. J. 25(4): 386-413 (2022) - [j21]Shuai Wang, Harrisen Scells, Bevan Koopman, Guido Zuccon:
Automated MeSH term suggestion for effective query formulation in systematic reviews literature search. Intell. Syst. Appl. 16: 200141 (2022) - [c178]Hang Li, Shengyao Zhuang, Xueguang Ma, Jimmy Lin, Guido Zuccon:
Pseudo-Relevance Feedback with Dense Retrievers in Pyserini. ADCS 2022: 1:1-1:6 - [c177]Shuai Wang, Harrisen Scells, Bevan Koopman, Guido Zuccon:
Neural Rankers for Effective Screening Prioritisation in Medical Systematic Review Literature Search. ADCS 2022: 4:1-4:10 - [c176]Gineke Wiggers, Guido Zuccon:
The Task: Distinguishing Tasks and Sessions in Legal Information Retrieval. ADCS 2022: 5:1-5:4 - [c175]Shengyao Zhuang, Xinyu Mao, Guido Zuccon:
Robustness of Neural Rankers to Typos: A Comparative Study. ADCS 2022: 6:1-6:6 - [c174]Sitthichoke Subpaiboonkit, Xue Li, Xin Zhao, Guido Zuccon:
Causality Discovery Based on Combined Causes and Multiple Causes in Drug-Drug Interaction. ADMA (1) 2022: 53-66 - [c173]Linh Le, Guido Zuccon, Genghong Zhao, Gianluca Demartini, Xia Zhang:
Leveraging Semantic Type Dependencies for Medical Named Entity Recognition. AMIA 2022 - [c172]Bing Liu, Wen Hua, Guido Zuccon, Genghong Zhao, Xia Zhang:
High-quality Task Division for Large-scale Entity Alignment. CIKM 2022: 1258-1268 - [c171]Ismail Sabei, Ahmed Mourad, Guido Zuccon:
SCC - A Test Collection for Search in Chat Conversations. CIKM 2022: 4429-4433 - [c170]Guido Zuccon:
Pretrained Language Models Rankers on Private Data: Is Online and Federated Learning the Solution? (short paper). DESIRES 2022: 35-39 - [c169]Hang Li, Shengyao Zhuang, Ahmed Mourad, Xueguang Ma, Jimmy Lin, Guido Zuccon:
Improving Query Representations for Dense Retrieval with Pseudo Relevance Feedback: A Reproducibility Study. ECIR (1) 2022: 599-612 - [c168]Shuai Wang, Harrisen Scells, Ahmed Mourad, Guido Zuccon:
Seed-Driven Document Ranking for Systematic Reviews: A Reproducibility Study. ECIR (1) 2022: 686-700 - [c167]Bing Liu, Harrisen Scells, Wen Hua, Guido Zuccon, Genghong Zhao, Xia Zhang:
Guiding Neural Entity Alignment with Compatibility. EMNLP 2022: 491-504 - [c166]Harrisen Scells, Connor Forbes, Justin Clark, Bevan Koopman, Guido Zuccon:
The Impact of Query Refinement on Systematic Review Literature Search: A Query Log Analysis. ICTIR 2022: 34-42 - [c165]Shengyao Zhuang, Hang Li, Guido Zuccon:
Implicit Feedback for Dense Passage Retrieval: A Counterfactual Approach. SIGIR 2022: 18-28 - [c164]Shengyao Zhuang, Guido Zuccon:
CharacterBERT and Self-Teaching for Improving the Robustness of Dense Retrievers on Queries with Typos. SIGIR 2022: 1444-1454 - [c163]Hang Li, Ahmed Mourad, Bevan Koopman, Guido Zuccon:
How Does Feedback Signal Quality Impact Effectiveness of Pseudo Relevance Feedback for Passage Retrieval. SIGIR 2022: 2154-2158 - [c162]Hang Li, Shuai Wang, Shengyao Zhuang, Ahmed Mourad, Xueguang Ma, Jimmy Lin, Guido Zuccon:
To Interpolate or not to Interpolate: PRF, Dense and Sparse Retrievers. SIGIR 2022: 2495-2500 - [c161]Shuyi Wang, Guido Zuccon:
Is Non-IID Data a Threat in Federated Online Learning to Rank? SIGIR 2022: 2801-2813 - [c160]Harrisen Scells, Shengyao Zhuang, Guido Zuccon:
Reduce, Reuse, Recycle: Green Information Retrieval Research. SIGIR 2022: 2825-2837 - [c159]Shuai Wang, Harrisen Scells, Justin Clark, Bevan Koopman, Guido Zuccon:
From Little Things Big Things Grow: A Collection with Seed Studies for Medical Systematic Review Literature Search. SIGIR 2022: 3176-3186 - [c158]Shengyao Zhuang, Guido Zuccon:
Asyncval: A Toolkit for Asynchronously Validating Dense Retriever Checkpoints During Training. SIGIR 2022: 3235-3239 - [c157]Ekaterina Khramtsova, Guido Zuccon, Xi Wang, Mahsa Baktashmotlagh:
Rethinking Persistent Homology For Visual Recognition. TAG-ML 2022: 206-215 - [i27]Shengyao Zhuang, Zhihao Qiao, Guido Zuccon:
Reinforcement Online Learning to Rank with Unbiased Reward Shaping. CoRR abs/2201.01534 (2022) - [i26]Daniel Locke, Guido Zuccon:
Case law retrieval: problems, methods, challenges and evaluations in the last 20 years. CoRR abs/2202.07209 (2022) - [i25]Shengyao Zhuang, Guido Zuccon:
Asyncval: A Toolkit for Asynchronously Validating Dense Retriever Checkpoints during Training. CoRR abs/2202.12510 (2022) - [i24]Shengyao Zhuang, Guido Zuccon:
CharacterBERT and Self-Teaching for Improving the Robustness of Dense Retrievers on Queries with Typos. CoRR abs/2204.00716 (2022) - [i23]Shengyao Zhuang, Hang Li, Guido Zuccon:
Implicit Feedback for Dense Passage Retrieval: A Counterfactual Approach. CoRR abs/2204.00718 (2022) - [i22]Shuai Wang, Harrisen Scells, Justin Clark, Bevan Koopman, Guido Zuccon:
From Little Things Big Things Grow: A Collection with Seed Studies for Medical Systematic Review Literature Search. CoRR abs/2204.03096 (2022) - [i21]Shuyi Wang, Guido Zuccon:
Is Non-IID Data a Threat in Federated Online Learning to Rank? CoRR abs/2204.09272 (2022) - [i20]Hang Li, Shuai Wang, Shengyao Zhuang, Ahmed Mourad, Xueguang Ma, Jimmy Lin, Guido Zuccon:
To Interpolate or not to Interpolate: PRF, Dense and Sparse Retrievers. CoRR abs/2205.00235 (2022) - [i19]Hang Li, Ahmed Mourad, Bevan Koopman, Guido Zuccon:
How does Feedback Signal Quality Impact Effectiveness of Pseudo Relevance Feedback for Passage Retrieval? CoRR abs/2205.05888 (2022) - [i18]Shengyao Zhuang, Houxing Ren, Linjun Shou, Jian Pei, Ming Gong, Guido Zuccon, Daxin Jiang:
Bridging the Gap Between Indexing and Retrieval for Differentiable Search Index with Query Generation. CoRR abs/2206.10128 (2022) - [i17]Ekaterina Khramtsova, Guido Zuccon, Xi Wang, Mahsa Baktashmotlagh:
Rethinking Persistent Homology for Visual Recognition. CoRR abs/2207.04220 (2022) - [i16]Bing Liu, Wen Hua, Guido Zuccon, Genghong Zhao, Xia Zhang:
High-quality Task Division for Large-scale Entity Alignment. CoRR abs/2208.10366 (2022) - [i15]Shuai Wang, Harrisen Scells, Bevan Koopman, Guido Zuccon:
Automated MeSH Term Suggestion for Effective Query Formulation in Systematic Reviews Literature Search. CoRR abs/2209.08687 (2022) - [i14]Bing Liu, Harrisen Scells, Wen Hua, Guido Zuccon, Genghong Zhao, Xia Zhang:
Guiding Neural Entity Alignment with Compatibility. CoRR abs/2211.15833 (2022) - [i13]Bing Liu, Tiancheng Lan, Wen Hua, Guido Zuccon:
Dependency-aware Self-training for Entity Alignment. CoRR abs/2211.16101 (2022) - [i12]Shuai Wang, Harrisen Scells, Bevan Koopman, Guido Zuccon:
Neural Rankers for Effective Screening Prioritisation in Medical Systematic Review Literature Search. CoRR abs/2212.09017 (2022) - [i11]Shuai Wang, Hang Li, Guido Zuccon:
MeSH Suggester: A Library and System for MeSH Term Suggestion for Systematic Review Boolean Query Construction. CoRR abs/2212.09018 (2022) - [i10]Bevan Koopman, Ahmed Mourad, Hang Li, Anton van der Vegt, Shengyao Zhuang, Simon Gibson, Yash Dang, David Lawrence, Guido Zuccon:
AgAsk: An Agent to Help Answer Farmer's Questions From Scientific Documents. CoRR abs/2212.10762 (2022) - 2021
- [j20]Harrisen Scells, Guido Zuccon, Bevan Koopman:
A comparison of automatic Boolean query formulation for systematic reviews. Inf. Retr. J. 24(1): 3-28 (2021) - [j19]Anton van der Vegt, Guido Zuccon, Bevan Koopman:
Do better search engines really equate to better clinical decisions? If not, why not? J. Assoc. Inf. Sci. Technol. 72(2): 141-155 (2021) - [j18]Aldo Lipani, David E. Losada, Guido Zuccon, Mihai Lupu:
Fixed-Cost Pooling Strategies. IEEE Trans. Knowl. Data Eng. 33(4): 1503-1522 (2021) - [c156]Bevan Koopman, Guido Zuccon:
Cohort-based Clinical Trial Retrieval. ADCS 2021: 3:1-3:9 - [c155]Shuai Wang, Hang Li, Harrisen Scells, Daniel Locke, Guido Zuccon:
MeSH Term Suggestion for Systematic Review Literature Search. ADCS 2021: 8:1-8:8 - [c154]Leif Azzopardi, Alistair Moffat, Paul Thomas, Guido Zuccon:
User Models, Metrics and Measures of Search: A Tutorial on the C/W/L Evaluation Framework. CHIIR 2021: 347-348 - [c153]Shuyi Wang, Shengyao Zhuang, Guido Zuccon:
Federated Online Learning to Rank with Evolution Strategies: A Reproducibility Study. ECIR (2) 2021: 134-149 - [c152]Bing Liu, Guido Zuccon, Wen Hua, Weitong Chen:
Diagnosis Ranking with Knowledge Graph Convolutional Networks. ECIR (1) 2021: 359-374 - [c151]Shengyao Zhuang, Hang Li, Guido Zuccon:
Deep Query Likelihood Model for Information Retrieval. ECIR (2) 2021: 463-470 - [c150]Shengyao Zhuang, Guido Zuccon:
Dealing with Typos for BERT-based Passage Retrieval and Ranking. EMNLP (1) 2021: 2836-2842 - [c149]Bing Liu, Harrisen Scells, Guido Zuccon, Wen Hua, Genghong Zhao:
ActiveEA: Active Learning for Neural Entity Alignment. EMNLP (1) 2021: 3364-3374 - [c148]Shuyi Wang, Bing Liu, Shengyao Zhuang, Guido Zuccon:
Effective and Privacy-preserving Federated Online Learning to Rank. ICTIR 2021: 3-12 - [c147]Shuai Wang, Shengyao Zhuang, Guido Zuccon:
BERT-based Dense Retrievers Require Interpolation with BM25 for Effective Passage Retrieval. ICTIR 2021: 317-324 - [c146]Guido Zuccon:
Session details: Session 3A - Queries. ICTIR 2021 - [c145]Le Thai Linh, Minh-Tien Nguyen, Guido Zuccon, Gianluca Demartini:
Loss-based Active Learning for Named Entity Recognition. IJCNN 2021: 1-8 - [c144]Shengyao Zhuang, Guido Zuccon:
How do Online Learning to Rank Methods Adapt to Changes of Intent? SIGIR 2021: 911-920 - [c143]Shengyao Zhuang, Guido Zuccon:
TILDE: Term Independent Likelihood moDEl for Passage Re-ranking. SIGIR 2021: 1483-1492 - [c142]Bevan Koopman, Tracey Wright, Natacha Omer, Veronica McCabe, Guido Zuccon:
Precision Medicine Search for Paediatric Oncology. SIGIR 2021: 2536-2540 - [c141]Harrisen Scells, Jimmy, Guido Zuccon:
Big Brother: A Drop-In Website Interaction Logging Service. SIGIR 2021: 2590-2594 - [c140]Kunpeng Qin, Harrisen Scells, Guido Zuccon:
PECAN: A Platform for Searching Chat Conversations. SIGIR 2021: 2610-2614 - [c139]Sebastian Cross, Ahmed Mourad, Guido Zuccon, Bevan Koopman:
Search Engines vs. Symptom Checkers: A Comparison of their Effectiveness for Online Health Advice. WWW 2021: 206-216 - [e5]Gianluca Demartini, Guido Zuccon, J. Shane Culpepper, Zi Huang, Hanghang Tong:
CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1 - 5, 2021. ACM 2021, ISBN 978-1-4503-8446-9 [contents] - [i9]Shengyao Zhuang, Guido Zuccon:
Fast Passage Re-ranking with Contextualized Exact Term Matching and Efficient Passage Expansion. CoRR abs/2108.08513 (2021) - [i8]Hang Li, Ahmed Mourad, Shengyao Zhuang, Bevan Koopman, Guido Zuccon:
Pseudo Relevance Feedback with Deep Language Models and Dense Retrievers: Successes and Pitfalls. CoRR abs/2108.11044 (2021) - [i7]Shengyao Zhuang, Guido Zuccon:
Dealing with Typos for BERT-based Passage Retrieval and Ranking. CoRR abs/2108.12139 (2021) - [i6]Bing Liu, Harrisen Scells, Guido Zuccon, Wen Hua, Genghong Zhao:
ActiveEA: Active Learning for Neural Entity Alignment. CoRR abs/2110.06474 (2021) - [i5]Shuai Wang, Hang Li, Harrisen Scells, Daniel Locke, Guido Zuccon:
MeSH Term Suggestion for Systematic Review Literature Search. CoRR abs/2112.00277 (2021) - [i4]Shuai Wang, Harrisen Scells, Ahmed Mourad, Guido Zuccon:
Seed-driven Document Ranking for Systematic Reviews: A Reproducibility Study. CoRR abs/2112.04090 (2021) - [i3]Hang Li, Shengyao Zhuang, Ahmed Mourad, Xueguang Ma, Jimmy Lin, Guido Zuccon:
Improving Query Representations for Dense Retrieval with Pseudo Relevance Feedback: A Reproducibility Study. CoRR abs/2112.06400 (2021) - 2020
- [j17]Suresh Pokharel, Guido Zuccon, Xue Li, Chandra Prasetyo Utomo, Yu Li:
Temporal tree representation for similarity computation between medical patients. Artif. Intell. Medicine 108: 101900 (2020) - [c138]Suresh Pokharel, Guido Zuccon, Yu Li:
Representing EHRs with Temporal Tree and Sequential Pattern Mining for Similarity Computing. ADMA 2020: 220-235 - [c137]Suresh Pokharel, Zhenkun Shi, Guido Zuccon, Yu Li:
Discriminative Features Generation for Mortality Prediction in ICU. ADMA 2020: 324-338 - [c136]Rischan Mafrur, Mohamed A. Sharaf, Guido Zuccon:
Quality Matters: Understanding the Impact of Incomplete Data on Visualization Recommendation. DEXA (1) 2020: 122-138 - [c135]Harrisen Scells, Guido Zuccon, Bevan Koopman, Justin Clark:
A Computational Approach for Objectively Derived Systematic Review Search Strategies. ECIR (1) 2020: 385-398 - [c134]Harrisen Scells, Guido Zuccon, Bevan Koopman:
You Can Teach an Old Dog New Tricks: Rank Fusion applied to Coordination Level Matching for Ranking in Systematic Reviews. ECIR (1) 2020: 399-414 - [c133]Shengyao Zhuang, Guido Zuccon:
Counterfactual Online Learning to Rank. ECIR (1) 2020: 415-430 - [c132]Hang Li, Harrisen Scells, Guido Zuccon:
Systematic Review Automation Tools for End-to-End Query Formulation. SIGIR 2020: 2141-2144 - [c131]Charles L. A. Clarke, Saira Rizvi, Mark D. Smucker, Maria Maistro, Guido Zuccon:
Overview of the TREC 2020 Health Misinformation Track. TREC 2020 - [c130]Sebastian Cross, Hang Li, Arvin Zhuang, Ahmed Mourad, Guido Zuccon, Bevan Koopman:
IELAB for TREC Conversational Assistance Track (CAsT) 2020. TREC 2020 - [c129]Harrisen Scells, Guido Zuccon, Bevan Koopman, Justin Clark:
Automatic Boolean Query Formulation for Systematic Review Literature Search. WWW 2020: 1071-1081 - [c128]Harrisen Scells, Guido Zuccon, Mohamed A. Sharaf, Bevan Koopman:
Sampling Query Variations for Learning to Rank to Improve Automatic Boolean Query Generation in Systematic Reviews. WWW 2020: 3041-3048
2010 – 2019
- 2019
- [j16]Jimmy, Guido Zuccon, Bevan Koopman:
Payoffs and pitfalls in using knowledge-bases for consumer health search. Inf. Retr. J. 22(3-4): 350-394 (2019) - [c127]Daniel Locke, Guido Zuccon:
Towards Automatically Classifying Case Law Citation Treatment Using Neural Networks. ADCS 2019: 4:1-4:8 - [c126]Sitthichoke Subpaiboonkit, Xue Li, Xin Zhao, Harrisen Scells, Guido Zuccon:
Causality Discovery with Domain Knowledge for Drug-Drug Interactions Discovery. ADMA 2019: 632-647 - [c125]Jimmy, Guido Zuccon, Bevan Koopman, Gianluca Demartini:
Health Cards to Assist Decision Making in Consumer Health Search. AMIA 2019 - [c124]Anton H. van der Vegt, Guido Zuccon, Bevan Koopman:
Learning Inter-Sentence, Disorder-Centric, Biomedical Relationships from Medical Literature. AMIA 2019 - [c123]Leif Azzopardi, Guido Zuccon:
Building Economic Models of Human Computer Interaction. CHI Extended Abstracts 2019 - [c122]Jimmy, Guido Zuccon, Bevan Koopman, Gianluca Demartini:
Health Card Retrieval for Consumer Health Search: An Empirical Investigation of Methods. CIKM 2019: 2405-2408 - [c121]Liadh Kelly, Hanna Suominen, Lorraine Goeuriot, Mariana L. Neves, Evangelos Kanoulas, Dan Li, Leif Azzopardi, René Spijker, Guido Zuccon, Harrisen Scells, João R. M. Palotti:
Overview of the CLEF eHealth Evaluation Lab 2019. CLEF 2019: 322-339 - [c120]