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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
- 2024
[c210]Linh Le
, Genghong Zhao, Xia Zhang, Guido Zuccon, Gianluca Demartini:
CoLAL: Co-learning Active Learning for Text Classification. AAAI 2024: 13337-13345- [c209]Shuyi Wang, Bing Liu, Guido Zuccon:
How to Forget Clients in Federated Online Learning to Rank? ECIR (3) 2024: 105-121 - [c208]Xinyu Mao, Bevan Koopman, Guido Zuccon:
A Reproducibility Study of Goldilocks: Just-Right Tuning of BERT for TAR. ECIR (4) 2024: 132-146 - [c207]Shuai Wang, Harrisen Scells, Shengyao Zhuang, Martin Potthast, Bevan Koopman, Guido Zuccon:
Zero-Shot Generative Large Language Models for Systematic Review Screening Automation. ECIR (1) 2024: 403-420 - [c206]Shengyao Zhuang, Honglei Zhuang, Bevan Koopman, Guido Zuccon:
A Setwise Approach for Effective and Highly Efficient Zero-shot Ranking with Large Language Models. SIGIR 2024: 38-47 - [c205]Watheq Mansour, Shengyao Zhuang, Guido Zuccon, Joel Mackenzie:
Revisiting Document Expansion and Filtering for Effective First-Stage Retrieval. SIGIR 2024: 186-196 - [c204]Shuai Wang, Ekaterina Khramtsova, Shengyao Zhuang, Guido Zuccon:
FeB4RAG: Evaluating Federated Search in the Context of Retrieval Augmented Generation. SIGIR 2024: 763-773 - [c203]Ekaterina Khramtsova, Shengyao Zhuang, Mahsa Baktashmotlagh, Guido Zuccon:
Leveraging LLMs for Unsupervised Dense Retriever Ranking. SIGIR 2024: 1307-1317 - [c202]Lukas Gienapp, Harrisen Scells, Niklas Deckers, Janek Bevendorff, Shuai Wang, Johannes Kiesel, Shahbaz Syed, Maik Fröbe, Guido Zuccon, Benno Stein, Matthias Hagen, Martin Potthast:
Evaluating Generative Ad Hoc Information Retrieval. SIGIR 2024: 1916-1929 - [c201]Xinyu Mao, Shengyao Zhuang, Bevan Koopman, Guido Zuccon:
Dense Retrieval with Continuous Explicit Feedback for Systematic Review Screening Prioritisation. SIGIR 2024: 2357-2362 - [c200]Shuai Wang, Shengyao Zhuang, Guido Zuccon:
Large Language Models Based Stemming for Information Retrieval: Promises, Pitfalls and Failures. SIGIR 2024: 2492-2496 - [c199]Ekaterina Khramtsova, Teerapong Leelanupab, Shengyao Zhuang, Mahsa Baktashmotlagh, Guido Zuccon:
Embark on DenseQuest: A System for Selecting the Best Dense Retriever for a Custom Collection. SIGIR 2024: 2739-2743 - [c198]Linh Le, Minh-Tien Nguyen, Khai Phan Tran, Genghong Zhao, Xia Zhang, Guido Zuccon, Gianluca Demartini:
Stochastic Featurization for Active Learning. TAI4H 2024: 52-65 - [e6]Grace Hui Yang, Hongning Wang, Sam Han, Claudia Hauff, Guido Zuccon, Yi Zhang:
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2024, Washington DC, USA, July 14-18, 2024. ACM 2024 [contents] - [i60]Shengyao Zhuang, Bevan Koopman, Guido Zuccon:
Team IELAB at TREC Clinical Trial Track 2023: Enhancing Clinical Trial Retrieval with Neural Rankers and Large Language Models. CoRR abs/2401.01566 (2024) - [i59]Shuai Wang, Harrisen Scells, Shengyao Zhuang, Martin Potthast, Bevan Koopman, Guido Zuccon:
Zero-shot Generative Large Language Models for Systematic Review Screening Automation. CoRR abs/2401.06320 (2024) - [i58]Xinyu Mao, Bevan Koopman, Guido Zuccon:
A Reproducibility Study of Goldilocks: Just-Right Tuning of BERT for TAR. CoRR abs/2401.08104 (2024) - [i57]Shuyi Wang, Bing Liu, Guido Zuccon:
How to Forget Clients in Federated Online Learning to Rank? CoRR abs/2401.13410 (2024) - [i56]Chuting Yu, Hang Li, Ahmed Mourad, Bevan Koopman, Guido Zuccon:
TPRF: A Transformer-based Pseudo-Relevance Feedback Model for Efficient and Effective Retrieval. CoRR abs/2401.13509 (2024) - [i55]Shuai Wang, Shengyao Zhuang, Bevan Koopman, Guido Zuccon:
ReSLLM: Large Language Models are Strong Resource Selectors for Federated Search. CoRR abs/2401.17645 (2024) - [i54]Ekaterina Khramtsova, Shengyao Zhuang, Mahsa Baktashmotlagh, Guido Zuccon:
Leveraging LLMs for Unsupervised Dense Retriever Ranking. CoRR abs/2402.04853 (2024) - [i53]Shuai Wang, Shengyao Zhuang, Guido Zuccon:
Large Language Models for Stemming: Promises, Pitfalls and Failures. CoRR abs/2402.11757 (2024) - [i52]Shuai Wang, Ekaterina Khramtsova, Shengyao Zhuang, Guido Zuccon:
FeB4RAG: Evaluating Federated Search in the Context of Retrieval Augmented Generation. CoRR abs/2402.11891 (2024) - [i51]Shengyao Zhuang, Bevan Koopman, Xiaoran Chu, Guido Zuccon:
Understanding and Mitigating the Threat of Vec2Text to Dense Retrieval Systems. CoRR abs/2402.12784 (2024) - [i50]Ferdinand Schlatt, Maik Fröbe, Harrisen Scells, Shengyao Zhuang, Bevan Koopman, Guido Zuccon, Benno Stein, Martin Potthast, Matthias Hagen:
Set-Encoder: Permutation-Invariant Inter-Passage Attention for Listwise Passage Re-Ranking with Cross-Encoders. CoRR abs/2404.06912 (2024) - [i49]Shengyao Zhuang, Xueguang Ma, Bevan Koopman, Jimmy Lin, Guido Zuccon:
PromptReps: Prompting Large Language Models to Generate Dense and Sparse Representations for Zero-Shot Document Retrieval. CoRR abs/2404.18424 (2024) - [i48]Ferdinand Schlatt, Maik Fröbe, Harrisen Scells, Shengyao Zhuang, Bevan Koopman, Guido Zuccon, Benno Stein, Martin Potthast, Matthias Hagen:
A Systematic Investigation of Distilling Large Language Models into Cross-Encoders for Passage Re-ranking. CoRR abs/2405.07920 (2024) - [i47]Shuoqi Sun, Shengyao Zhuang, Shuai Wang, Guido Zuccon:
An Investigation of Prompt Variations for Zero-shot LLM-based Rankers. CoRR abs/2406.14117 (2024) - [i46]Xinyu Mao, Shengyao Zhuang, Bevan Koopman, Guido Zuccon:
Dense Retrieval with Continuous Explicit Feedback for Systematic Review Screening Prioritisation. CoRR abs/2407.00635 (2024) - [i45]Ekaterina Khramtsova, Teerapong Leelanupab, Shengyao Zhuang, Mahsa Baktashmotlagh, Guido Zuccon:
Embark on DenseQuest: A System for Selecting the Best Dense Retriever for a Custom Collection. CoRR abs/2407.06685 (2024) - [i44]Ekaterina Khramtsova, Mahsa Baktashmotlagh, Guido Zuccon, Xi Wang, Mathieu Salzmann:
Source-Free Domain-Invariant Performance Prediction. CoRR abs/2408.02209 (2024) - 2023
- [j26]Mohamed A. Sharaf, Rischan Mafrur, Guido Zuccon:
Efficient Diversification for Recommending Aggregate Data Visualizations. IEEE Access 11: 62261-62280 (2023) - [j25]Linh Le, Gianluca Demartini, Guido Zuccon, Genghong Zhao, Xia Zhang:
Active learning with feature matching for clinical named entity recognition. Nat. Lang. Process. J. 4: 100015 (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) - [c197]Ekaterina Khramtsova, Guido Zuccon, Xi Wang, Mahsa Baktashmotlagh:
Convolutional Persistence as a Remedy to Neural Model Analysis. AISTATS 2023: 10839-10855 - [c196]Sebastian Cross, Guido Zuccon, Ahmed Mourad:
A Reproducibility Study of Question Retrieval for Clarifying Questions. ECIR (3) 2023: 35-50 - [c195]Shengyao Zhuang, Bing Liu, Bevan Koopman, Guido Zuccon:
Open-source Large Language Models are Strong Zero-shot Query Likelihood Models for Document Ranking. EMNLP (Findings) 2023: 8807-8817 - [c194]Bevan Koopman, Guido Zuccon:
Dr ChatGPT tell me what I want to hear: How different prompts impact health answer correctness. EMNLP 2023: 15012-15022 - [c193]Wojciech Kusa, Guido Zuccon, Petr Knoth, Allan Hanbury:
Outcome-based Evaluation of Systematic Review Automation. ICTIR 2023: 125-133 - [c192]Joel Mackenzie, Shengyao Zhuang, Guido Zuccon:
Exploring the Representation Power of SPLADE Models. ICTIR 2023: 143-147 - [c191]Shuyi Wang, Guido Zuccon:
An Analysis of Untargeted Poisoning Attack and Defense Methods for Federated Online Learning to Rank Systems. ICTIR 2023: 215-224 - [c190]Guido Zuccon, Harrisen Scells, Shengyao Zhuang:
Beyond CO2 Emissions: The Overlooked Impact of Water Consumption of Information Retrieval Models. ICTIR 2023: 283-289 - [c189]Shuai Wang, Harrisen Scells, Bevan Koopman, Guido Zuccon:
Can ChatGPT Write a Good Boolean Query for Systematic Review Literature Search? SIGIR 2023: 1426-1436 - [c188]Shengyao Zhuang, Linjun Shou, Guido Zuccon:
Augmenting Passage Representations with Query Generation for Enhanced Cross-Lingual Dense Retrieval. SIGIR 2023: 1827-1832 - [c187]Shuai Wang, Guido Zuccon:
Balanced Topic Aware Sampling for Effective Dense Retriever: A Reproducibility Study. SIGIR 2023: 2542-2551 - [c186]Guido Zuccon, Bevan Koopman, Razia Shaik:
ChatGPT Hallucinates when Attributing Answers. SIGIR-AP 2023: 46-51 - [c185]Shuai Wang, Harrisen Scells, Bevan Koopman, Martin Potthast, Guido Zuccon:
Generating Natural Language Queries for More Effective Systematic Review Screening Prioritisation. SIGIR-AP 2023: 73-83 - [c184]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. SIGIR-AP 2023: 139-149 - [c183]Shengyao Zhuang, Linjun Shou, Jian Pei, Ming Gong, Houxing Ren, Guido Zuccon, Daxin Jiang:
Typos-aware Bottlenecked Pre-Training for Robust Dense Retrieval. SIGIR-AP 2023: 212-222 - [c182]Ekaterina Khramtsova, Shengyao Zhuang, Mahsa Baktashmotlagh, Xi Wang, Guido Zuccon:
Selecting which Dense Retriever to use for Zero-Shot Search. SIGIR-AP 2023: 223-233 - [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 - [i43]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) - [i42]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) - [i41]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) - [i40]Shengyao Zhuang, Linjun Shou, Guido Zuccon:
Augmenting Passage Representations with Query Generation for Enhanced Cross-Lingual Dense Retrieval. CoRR abs/2305.03950 (2023) - [i39]Guido Zuccon, Harrisen Scells, Shengyao Zhuang:
Beyond CO2 Emissions: The Overlooked Impact of Water Consumption of Information Retrieval Models. CoRR abs/2306.16668 (2023) - [i38]Joel Mackenzie, Shengyao Zhuang, Guido Zuccon:
Exploring the Representation Power of SPLADE Models. CoRR abs/2306.16680 (2023) - [i37]Wojciech Kusa, Guido Zuccon, Petr Knoth, Allan Hanbury:
Outcome-based Evaluation of Systematic Review Automation. CoRR abs/2306.17614 (2023) - [i36]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) - [i35]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) - [i34]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) - [i33]Guido Zuccon, Bevan Koopman, Razia Shaik:
ChatGPT Hallucinates when Attributing Answers. CoRR abs/2309.09401 (2023) - [i32]Ekaterina Khramtsova, Shengyao Zhuang, Mahsa Baktashmotlagh, Xi Wang, Guido Zuccon:
Selecting which Dense Retriever to use for Zero-Shot Search. CoRR abs/2309.09403 (2023) - [i31]Shengyao Zhuang, Honglei Zhuang, Bevan Koopman, Guido Zuccon:
A Setwise Approach for Effective and Highly Efficient Zero-shot Ranking with Large Language Models. CoRR abs/2310.09497 (2023) - [i30]Shengyao Zhuang, Bing Liu, Bevan Koopman, Guido Zuccon:
Open-source Large Language Models are Strong Zero-shot Query Likelihood Models for Document Ranking. CoRR abs/2310.13243 (2023) - [i29]Lukas Gienapp, Harrisen Scells, Niklas Deckers, Janek Bevendorff, Shuai Wang, Johannes Kiesel, Shahbaz Syed, Maik Fröbe, Guido Zuccon, Benno Stein, Matthias Hagen, Martin Potthast:
Evaluating Generative Ad Hoc Information Retrieval. CoRR abs/2311.04694 (2023) - [i28]Rischan Mafrur, Mohamed A. Sharaf, Guido Zuccon:
VizPut: Insight-Aware Imputation of Incomplete Data for Visualization Recommendation. CoRR abs/2311.07926 (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]Liadh Kelly, Lorraine Goeuriot, Hanna Suominen, Mariana L. Neves, Evangelos Kanoulas, René Spijker, Leif Azzopardi, Dan Li, Jimmy, João R. M. Palotti, Guido Zuccon:
CLEF eHealth 2019 Evaluation Lab. ECIR (2) 2019: 267-274 - [c119]Jimmy, Guido Zuccon, Bevan Koopman, Gianluca Demartini:
Health Cards for Consumer Health Search. SIGIR 2019: 35-44 - [c118]Harrisen Scells, Guido Zuccon:
ielab at the Open-Source IR Replicability Challenge 2019. OSIRRC@SIGIR 2019: 57-61 - [c117]João R. M. Palotti, Harrisen Scells, Guido Zuccon:
TrecTools: an Open-source Python Library for Information Retrieval Practitioners Involved in TREC-like Campaigns. SIGIR 2019: 1325-1328 - [c116]Leif Azzopardi, Alistair Moffat, Paul Thomas, Guido Zuccon:
Building Economic Models and Measures of Search. SIGIR 2019: 1401-1402 - [c115]Jimmy, Guido Zuccon:
UQ IElab at TREC 2019 Decision Track. TREC 2019 - [c114]Bevan Koopman, Guido Zuccon:
WSDM 2019 Tutorial on Health Search (HS2019): A Full-Day from Consumers to Clinicians. WSDM 2019: 838-839 - [c113]Harrisen Scells, Guido Zuccon, Bevan Koopman:
Automatic Boolean Query Refinement for Systematic Review Literature Search. WWW 2019: 1646-1656 - 2018
- [j15]Bevan Koopman, Guido Zuccon, Anthony N. Nguyen, Anton Bergheim, Narelle Grayson:
Extracting cancer mortality statistics from death certificates: A hybrid machine learning and rule-based approach for common and rare cancers. Artif. Intell. Medicine 89: 1-9 (2018) - [j14]Lorraine Goeuriot, Gareth J. F. Jones, Liadh Kelly, Johannes Leveling, Mihai Lupu, João R. M. Palotti, Guido Zuccon:
An analysis of evaluation campaigns in ad-hoc medical information retrieval: CLEF eHealth 2013 and 2014. Inf. Retr. J. 21(6): 507-540 (2018) - [j13]Anton van der Vegt, Guido Zuccon, Bevan Koopman, Peter Bruza:
A task completion framework to support single-interaction IR research. J. Documentation 74(2): 289-308 (2018) - [j12]Bevan Koopman, Jack Russell, Guido Zuccon:
Task-oriented search for evidence-based medicine. Int. J. Digit. Libr. 19(2-3): 217-229 (2018) - [c112]Dilesha Seneviratne, Shlomo Geva, Guido Zuccon, Gabriela Ferraro, Magali R. G. Meireles:
Linking Patents to Knowledge Sources: A Context Matching Technique using Automatic Patent Classification. ADCS 2018: 13:1-13:4 - [c111]João R. M. Palotti, Guido Zuccon, Allan Hanbury:
MM: A new Framework for Multidimensional Evaluation of Search Engines. CIKM 2018: 1699-1702 - [c110]Harrisen Scells, Guido Zuccon:
searchrefiner: A Query Visualisation and Understanding Tool for Systematic Reviews. CIKM 2018: 1939-1942 - [c109]Jimmy, Guido Zuccon, Bevan Koopman:
QUT IElab at CLEF 2018 Consumer Health Search Task: Knowledge Base Retrieval for Consumer Health Search. CLEF (Working Notes) 2018 - [c108]Jimmy, Guido Zuccon, João R. M. Palotti, Lorraine Goeuriot, Liadh Kelly:
Overview of the CLEF 2018 Consumer Health Search Task. CLEF (Working Notes) 2018 - [c107]Hanna Suominen, Liadh Kelly, Lorraine Goeuriot, Aurélie Névéol, Lionel Ramadier, Aude Robert, Evangelos Kanoulas, René Spijker, Leif Azzopardi, Dan Li, Jimmy, João R. M. Palotti, Guido Zuccon:
Overview of the CLEF eHealth Evaluation Lab 2018. CLEF 2018: 286-301 - [c106]Jimmy, Guido Zuccon, Bevan Koopman:
Choices in Knowledge-Base Retrieval for Consumer Health Search. ECIR 2018: 72-85 - [c105]Harrisen Scells, Guido Zuccon:
Generating Better Queries for Systematic Reviews. SIGIR 2018: 475-484 - [c104]Harrisen Scells, Leif Azzopardi, Guido Zuccon, Bevan Koopman:
Query Variation Performance Prediction for Systematic Reviews. SIGIR 2018: 1089-1092 - [c103]Jimmy, Guido Zuccon, Gianluca Demartini:
On the Volatility of Commercial Search Engines and its Impact on Information Retrieval Research. SIGIR 2018: 1105-1108 - [c102]Daniel Locke, Guido Zuccon:
A Test Collection for Evaluating Legal Case Law Search. SIGIR 2018: 1261-1264 - [c101]Harrisen Scells, Daniel Locke, Guido Zuccon:
An Information Retrieval Experiment Framework for Domain Specific Applications. SIGIR 2018: 1281-1284 - [c100]Guido Zuccon, Bevan Koopman:
SIGIR 2018 Tutorial on Health Search (HS2018): A Full-day from Consumers to Clinicians. SIGIR 2018: 1391-1394 - [i2]Dimitri Perrin, Guido Zuccon:
Recursive module extraction using Louvain and PageRank. F1000Research 7: 1286 (2018) - 2017
- [j11]Mahnoosh Kholghi, Laurianne Sitbon, Guido Zuccon, Anthony N. Nguyen:
Active learning reduces annotation time for clinical concept extraction. Int. J. Medical Informatics 106: 25-31 (2017) - [j10]Mahnoosh Kholghi, Lance De Vine, Laurianne Sitbon, Guido Zuccon, Anthony N. Nguyen:
Clinical information extraction using small data: An active learning approach based on sequence representations and word embeddings. J. Assoc. Inf. Sci. Technol. 68(11): 2543-2556 (2017) - [j9]Bevan Koopman, Guido Zuccon, Peter Bruza:
What makes an effective clinical query and querier? J. Assoc. Inf. Sci. Technol. 68(11): 2557-2571 (2017) - [c99]Dilesha Seneviratne, Shlomo Geva, Guido Zuccon, Andrew Trotman:
An Initial Study of Anchor Selection in Patent Link Discovery. ADCS 2017: 10:1-10:4 - [c98]Daniel Locke, Guido Zuccon, Harrisen Scells:
Automatic Query Generation from Legal Texts for Case Law Retrieval. AIRS 2017: 181-193 - [c97]Harrisen Scells, Guido Zuccon, Bevan Koopman, Anthony Deacon, Leif Azzopardi, Shlomo Geva:
Integrating the Framing of Clinical Questions via PICO into the Retrieval of Medical Literature for Systematic Reviews. CIKM 2017: 2291-2294 - [c96]Lorraine Goeuriot, Liadh Kelly, Hanna Suominen, Aurélie Névéol, Aude Robert, Evangelos Kanoulas, René Spijker, João R. M. Palotti, Guido Zuccon:
CLEF 2017 eHealth Evaluation Lab Overview. CLEF 2017: 291-303 - [c95]Jimmy, Guido Zuccon, Bevan Koopman:
QUT ielab at CLEF 2017 e-Health IR Task: Knowledge Base Retrieval for Consumer Health Search. CLEF (Working Notes) 2017 - [c94]João R. M. Palotti, Guido Zuccon, Jimmy, Pavel Pecina, Mihai Lupu, Lorraine Goeuriot, Liadh Kelly, Allan Hanbury:
CLEF 2017 Task Overview: The IR Task at the eHealth Evaluation Lab - Evaluating Retrieval Methods for Consumer Health Search. CLEF (Working Notes) 2017 - [c93]Harrisen Scells, Guido Zuccon, Anthony Deacon, Bevan Koopman:
QUT ielab at CLEF 2017 Technology Assisted Reviews Track: Initial Experiments with Learning To Rank. CLEF (Working Notes) 2017 - [c92]Aldo Lipani, João R. M. Palotti, Mihai Lupu, Florina Piroi, Guido Zuccon, Allan Hanbury:
Fixed-Cost Pooling Strategies Based on IR Evaluation Measures. ECIR 2017: 357-368 - [c91]Daniel Locke, Guido Zuccon:
Automatic Cited Decision Retrieval: Working notes of Ielab for FIRE Legal Track Precedence Retrieval Task. FIRE (Working Notes) 2017: 80-81 - [c90]Sebastian Cross, Zak Waters, Kirsty Kitto, Guido Zuccon:
Classifying help seeking behaviour in online communities. LAK 2017: 419-423 - [c89]Aldo Lipani, Mihai Lupu, João R. M. Palotti, Guido Zuccon, Allan Hanbury:
Fixed budget pooling strategies based on fusion methods. SAC 2017: 919-924 - [c88]Bevan Koopman, Liam Cripwell, Guido Zuccon:
Generating Clinical Queries from Patient Narratives: A Comparison between Machines and Humans. SIGIR 2017: 853-856 - [c87]Harrisen Scells, Guido Zuccon, Bevan Koopman, Anthony Deacon, Leif Azzopardi, Shlomo Geva:
A Test Collection for Evaluating Retrieval of Studies for Inclusion in Systematic Reviews. SIGIR 2017: 1237-1240 - [c86]Bevan Koopman, Guido Zuccon, Jack Russell:
A Task-oriented Search Engine for Evidence-based Medicine. SIGIR 2017: 1329-1332 - [c85]Guido Zuccon, Bevan Koopman:
SIGIR 2017 Tutorial on Health Search (HS2017): A Full-day from Consumers to Clinicians. SIGIR 2017: 1415-1418 - [c84]Leif Azzopardi, Matt Crane, Hui Fang, Grant Ingersoll, Jimmy Lin, Yashar Moshfeghi, Harrisen Scells, Peilin Yang, Guido Zuccon:
The Lucene for Information Access and Retrieval Research (LIARR) Workshop at SIGIR 2017. SIGIR 2017: 1429-1430 - [e4]Bevan Koopman, Guido Zuccon, Mark James Carman:
Proceedings of the 22nd Australasian Document Computing Symposium, ADCS 2017, Brisbane, QLD, Australia, December 7-8, 2017. ACM 2017, ISBN 978-1-4503-6391-4 [contents] - 2016
- [j8]Bevan Koopman, Guido Zuccon, Peter Bruza, Laurianne Sitbon, Michael Lawley:
Information retrieval as semantic inference: a Graph Inference model applied to medical search. Inf. Retr. J. 19(1-2): 6-37 (2016) - [j7]Mahnoosh Kholghi, Laurianne Sitbon, Guido Zuccon, Anthony N. Nguyen:
Active learning: a step towards automating medical concept extraction. J. Am. Medical Informatics Assoc. 23(2): 289-296 (2016) - [c83]Mahnoosh Kholghi, Lance De Vine, Laurianne Sitbon, Guido Zuccon, Anthony N. Nguyen:
The Benefits of Word Embeddings Features for Active Learning in Clinical Information Extraction. ALTA 2016: 25-34 - [c82]Jimmy, Guido Zuccon, Bevan Koopman:
Boosting Titles does not Generally Improve Retrieval Effectiveness. ADCS 2016: 25-32 - [c81]Dinesha Chathurani Nanayakkara Wasam Uluwitige, Shlomo Geva, Guido Zuccon, Vinod Chandran, Timothy Chappell:
Effective User Relevance Feedback for Image Retrieval with Image Signatures. ADCS 2016: 49-56 - [c80]Guido Zuccon, João R. M. Palotti, Allan Hanbury:
Query Variations and their Effect on Comparing Information Retrieval Systems. CIKM 2016: 691-700 - [c79]Navid Rekabsaz, Mihai Lupu, Allan Hanbury, Guido Zuccon:
Generalizing Translation Models in the Probabilistic Relevance Framework. CIKM 2016: 711-720 - [c78]Guido Zuccon, João R. M. Palotti, Lorraine Goeuriot, Liadh Kelly, Mihai Lupu, Pavel Pecina, Henning Müller, Julie Budaher, Anthony Deacon:
The IR Task at the CLEF eHealth Evaluation Lab 2016: User-centred Health Information Retrieval. CLEF (Working Notes) 2016: 15-27 - [c77]João R. M. Palotti, Guido Zuccon, Johannes Bernhardt-Melischnig, Allan Hanbury, Lorraine Goeuriot:
Assessors Agreement: A Case Study Across Assessor Type, Payment Levels, Query Variations and Relevance Dimensions. CLEF 2016: 40-53 - [c76]Liadh Kelly, Lorraine Goeuriot, Hanna Suominen, Aurélie Névéol, João R. M. Palotti, Guido Zuccon:
Overview of the CLEF eHealth Evaluation Lab 2016. CLEF 2016: 255-266 - [c75]Guido Zuccon:
Understandability Biased Evaluation for Information Retrieval. ECIR 2016: 280-292 - [c74]Leif Azzopardi, Guido Zuccon:
Two Scrolls or One Click: A Cost Model for Browsing Search Results. ECIR 2016: 696-702 - [c73]Leif Azzopardi, Guido Zuccon:
Advances in Formal Models of Search and Search Behaviour. ICTIR 2016: 1-4 - [c72]Leif Azzopardi, Guido Zuccon:
An Analysis of the Cost and Benefit of Search Interactions. ICTIR 2016: 59-68 - [c71]Aldo Lipani, Guido Zuccon, Mihai Lupu, Bevan Koopman, Allan Hanbury:
The Impact of Fixed-Cost Pooling Strategies on Test Collection Bias. ICTIR 2016: 105-108 - [c70]Lorraine Goeuriot, Liadh Kelly, Guido Zuccon, João R. M. Palotti:
Building Evaluation Datasets for Consumer-Oriented Information Retrieval. LREC 2016 - [c69]Harrisen Scells, Guido Zuccon, Kirsty Kitto:
QUT at the NTCIR Lifelog Semantic Access Task. NTCIR 2016 - [c68]Bevan Koopman, Guido Zuccon:
A Test Collection for Matching Patients to Clinical Trials. SIGIR 2016: 669-672 - [c67]João R. M. Palotti, Lorraine Goeuriot, Guido Zuccon, Allan Hanbury:
Ranking Health Web Pages with Relevance and Understandability. SIGIR 2016: 965-968 - [i1]Mahnoosh Kholghi, Lance De Vine, Laurianne Sitbon, Guido Zuccon, Anthony N. Nguyen:
The benefits of word embeddings features for active learning in clinical information extraction. CoRR abs/1607.02810 (2016) - 2015
- [j6]Guido Zuccon, Sankalp Khanna, Anthony N. Nguyen, Justin R. Boyle, Matthew Hamlet, Mark A. Cameron:
Automatic detection of tweets reporting cases of influenza like illnesses in Australia. Health Inf. Sci. Syst. 3(1) (2015) - [j5]Bevan Koopman, Guido Zuccon, Anthony N. Nguyen, Anton Bergheim, Narelle Grayson:
Automatic ICD-10 classification of cancers from free-text death certificates. Int. J. Medical Informatics 84(11): 956-965 (2015) - [c66]Lance De Vine, Mahnoosh Kholghi, Guido Zuccon, Laurianne Sitbon, Anthony N. Nguyen:
Analysis of Word Embeddings and Sequence Features for Clinical Information Extraction. ALTA 2015: 21-30 - [c65]Guido Zuccon, Bevan Koopman, Peter Bruza, Leif Azzopardi:
Integrating and Evaluating Neural Word Embeddings in Information Retrieval. ADCS 2015: 12:1-12:8 - [c64]Dilesha Seneviratne, Shlomo Geva, Guido Zuccon, Gabriela Ferraro, Timothy Chappell, Magali R. G. Meireles:
A Signature Approach to Patent Classification. AIRS 2015: 413-419 - [c63]Hamed Tayebikhorami, Alejandro Metke-Jimenez, Anthony N. Nguyen, Guido Zuccon:
Oyster: A Tool for Fine-Grained Ontological Annotations in Free-Text. AIRS 2015: 440-446 - [c62]Bevan Koopman, Guido Zuccon, Amol Wagholikar, Kevin Chu, John O'Dwyer, Anthony N. Nguyen, Gerben Keijzers:
Automated Reconciliation of Radiology Reports and Discharge Summaries. AMIA 2015 - [c61]Mahnoosh Kholghi, Laurianne Sitbon, Guido Zuccon, Anthony N. Nguyen:
External Knowledge and Query Strategies in Active Learning: a Study in Clinical Information Extraction. CIKM 2015: 143-152 - [c60]João Rafael De Moura Palotti, Guido Zuccon, Allan Hanbury:
The Influence of Pre-processing on the Estimation of Readability of Web Documents. CIKM 2015: 1763-1766 - [c59]Lorraine Goeuriot, Liadh Kelly, Hanna Suominen, Leif Hanlen, Aurélie Névéol, Cyril Grouin, João R. M. Palotti, Guido Zuccon:
Overview of the CLEF eHealth Evaluation Lab 2015. CLEF 2015: 429-443 - [c58]João R. M. Palotti, Guido Zuccon, Lorraine Goeuriot, Liadh Kelly, Allan Hanbury, Gareth J. F. Jones, Mihai Lupu, Pavel Pecina:
CLEF eHealth Evaluation Lab 2015, Task 2: Retrieving Information About Medical Symptoms. CLEF (Working Notes) 2015 - [c57]Timothy Chappell, Shlomo Geva, Guido Zuccon:
Approximate Nearest-Neighbour Search with Inverted Signature Slice Lists. ECIR 2015: 147-158 - [c56]Guido Zuccon, Bevan Koopman, João R. M. Palotti:
Diagnose This If You Can - On the Effectiveness of Search Engines in Finding Medical Self-diagnosis Information. ECIR 2015: 562-567 - [c55]Leif Azzopardi, Guido Zuccon:
An Analysis of Theories of Search and Search Behavior. ICTIR 2015: 81-90 - [c54]Leif Azzopardi, Guido Zuccon:
Building and Using Models of Information Seeking, Search and Retrieval: Full Day Tutorial. SIGIR 2015: 1107-1110 - [e3]Guido Zuccon, Shlomo Geva, Hideo Joho, Falk Scholer, Aixin Sun, Peng Zhang:
Information Retrieval Technology - 11th Asia Information Retrieval Societies Conference, AIRS 2015, Brisbane, QLD, Australia, December 2-4, 2015. Proceedings. Lecture Notes in Computer Science 9460, Springer 2015, ISBN 978-3-319-28939-7 [contents] - 2014
- [j4]Guido Zuccon, Daniel Kotzur, Anthony N. Nguyen, Anton Bergheim:
De-identification of health records using Anonym: Effectiveness and robustness across datasets. Artif. Intell. Medicine 61(3): 145-151 (2014) - [j3]Michael Symonds, Peter Bruza, Guido Zuccon, Bevan Koopman, Laurianne Sitbon, Ian W. Turner:
Automatic query expansion: A structural linguistic perspective. J. Assoc. Inf. Sci. Technol. 65(8): 1577-1596 (2014) - [c53]Bevan Koopman, Guido Zuccon:
Document Timespan Normalisation and Understanding Temporality for Clinical Records Search. ADCS 2014: 85 - [c52]Shahin Mirhosseini, Guido Zuccon, Bevan Koopman, Anthony N. Nguyen, Michael Lawley:
Medical Free-Text to Concept Mapping as an Information Retrieval Problem. ADCS 2014: 93 - [c51]Mahnoosh Kholghi, Laurianne Sitbon, Guido Zuccon, Anthony N. Nguyen:
Factors Influencing Robustness and Effectiveness of Conditional Random Fields in Active Learning Frameworks. AusDM 2014: 69-78 - [c50]Guido Zuccon, Bevan Koopman, Peter Bruza:
Exploiting Inference from Semantic Annotations for Information Retrieval: Reflections From Medical IR. ESAIR 2014: 43-45 - [c49]Lance De Vine, Guido Zuccon, Bevan Koopman, Laurianne Sitbon, Peter Bruza:
Medical Semantic Similarity with a Neural Language Model. CIKM 2014: 1819-1822 - [c48]Lorraine Goeuriot, Liadh Kelly, Wei Li, João R. M. Palotti, Pavel Pecina, Guido Zuccon, Allan Hanbury, Gareth J. F. Jones, Henning Müller:
ShARe/CLEF eHealth Evaluation Lab 2014, Task 3: User-centred Health Information Retrieval. CLEF (Working Notes) 2014: 43-61 - [c47]Liadh Kelly, Lorraine Goeuriot, Hanna Suominen, Tobias Schreck, Gondy Leroy, Danielle L. Mowery, Sumithra Velupillai, Wendy W. Chapman, David Martínez, Guido Zuccon, João R. M. Palotti:
Overview of the ShARe/CLEF eHealth Evaluation Lab 2014. CLEF 2014: 172-191 - [c46]Bevan Koopman, Guido Zuccon:
Why Assessing Relevance in Medical IR is Demanding. MedIR@SIGIR 2014: 16-19 - [c45]Guido Zuccon, Bevan Koopman:
Integrating Understandability in the Evaluation of Consumer Health Search Engines. MedIR@SIGIR 2014: 32-35 - [c44]Bevan Koopman, Guido Zuccon:
Understanding negation and family history to improve clinical information retrieval. SIGIR 2014: 971-974 - [c43]Bevan Koopman, Guido Zuccon:
Relevation!: an open source system for information retrieval relevance assessment}. SIGIR 2014: 1243-1244 - [e2]J. Shane Culpepper, Laurence Anthony F. Park, Guido Zuccon:
Proceedings of the 2014 Australasian Document Computing Symposium, ADCS 2014, Melbourne, VIC, Australia, November 27-28, 2014. ACM 2014, ISBN 978-1-4503-3000-8 [contents] - 2013
- [j2]Guido Zuccon, Teerapong Leelanupab, Stewart Whiting, Emine Yilmaz, Joemon M. Jose, Leif Azzopardi:
Crowdsourcing interactions: using crowdsourcing for evaluating interactive information retrieval systems. Inf. Retr. 16(2): 267-305 (2013) - [j1]Guido Zuccon:
Document ranking with quantum probabilities. SIGIR Forum 47(1): 69-70 (2013) - [c42]Timothy Chappell, Shlomo Geva, Anthony N. Nguyen, Guido Zuccon:
Efficient top-k retrieval with signatures. ADCS 2013: 10-17 - [c41]Bevan Koopman, Guido Zuccon, Lance De Vine, Aneesha Bakharia, Peter Bruza, Laurianne Sitbon, Andrew Gibson:
ADCS reaches adulthood: an analysis of the conference and its community over the last eighteen years. ADCS 2013: 34-41 - [c40]Lavish Lalwani, Guido Zuccon, Mohamed A. Sharaf, Anthony N. Nguyen:
Towards a Visually Enhanced Medical Search Engine. AIH+CARE@AUS-AI 2013: 22-38 - [c39]Michael Symonds, Guido Zuccon, Bevan Koopman, Peter Bruza, Laurianne Sitbon:
Term associations in query expansion: a structural linguistic perspective. CIKM 2013: 1189-1192 - [c38]Lorraine Goeuriot, Gareth J. F. Jones, Liadh Kelly, Johannes Leveling, Allan Hanbury, Henning Müller, Sanna Salanterä, Hanna Suominen, Guido Zuccon:
ShARe/CLEF eHealth Evaluation Lab 2013, Task 3: Information Retrieval to Address Patients' Questions when Reading Clinical Reports. CLEF (Working Notes) 2013 - [c37]Hanna Suominen, Sanna Salanterä, Sumithra Velupillai, Wendy Webber Chapman, Guergana K. Savova, Noemie Elhadad, Sameer Pradhan, Brett R. South, Danielle L. Mowery, Gareth J. F. Jones, Johannes Leveling, Liadh Kelly, Lorraine Goeuriot, David Martínez, Guido Zuccon:
Overview of the ShARe/CLEF eHealth Evaluation Lab 2013. CLEF 2013: 212-231 - [c36]Guido Zuccon, Alexander Holloway, Bevan Koopman, Anthony N. Nguyen:
Identify Disorders in Health Records using Conditional Random Fields and Metamap AEHRC at ShARe/CLEF 2013 eHealth Evaluation Lab Task 1. CLEF (Working Notes) 2013 - [c35]Guido Zuccon, Bevan Koopman, Anthony N. Nguyen:
Retrieval of Health Advice on the Web AEHRC at ShARe/CLEF eHealth Evaluation Lab Task 3. CLEF (Working Notes) 2013 - [c34]Teerapong Leelanupab, Guido Zuccon, Joemon M. Jose:
Is Intent-Aware Expected Reciprocal Rank Sufficient to Evaluate Diversity? ECIR 2013: 738-742 - [c33]Lorraine Goeuriot, Liadh Kelly, Gareth J. F. Jones, Guido Zuccon, Hanna Suominen, Allan Hanbury, Henning Müller, Johannes Leveling:
Creation of a New Evaluation Benchmark for Information Retrieval Targeting Patient Information Needs. EVIA@NTCIR 2013 - [c32]Peter Wittek, Bevan Koopman, Guido Zuccon, Sándor Darányi:
Combining Word Semantics within Complex Hilbert Space for Information Retrieval. QI 2013: 160-171 - [e1]J. Shane Culpepper, Guido Zuccon, Laurianne Sitbon:
The Australasian Document Computing Symposium, ADCS '13, Brisbane, QLD, Australia, December 5-6, 2013. ACM 2013, ISBN 978-1-4503-2524-0 [contents] - 2012
- [b1]Guido Zuccon:
Document ranking with quantum probabilities. University of Glasgow, UK, 2012 - [c31]Michael Symonds, Guido Zuccon, Bevan Koopman, Peter Bruza, Anthony N. Nguyen:
Semantic Judgement of Medical Concepts: Combining Syntagmatic and Paradigmatic Information with the Tensor Encoding Model. ALTA 2012: 15-22 - [c30]Bevan Koopman, Guido Zuccon, Peter Bruza, Laurianne Sitbon, Michael Lawley:
Graph-based concept weighting for medical information retrieval. ADCS 2012: 80-87 - [c29]Guido Zuccon, Bevan Koopman, Anthony N. Nguyen, Deanne Vickers, Luke Butt:
Exploiting medical hierarchies for concept-based information retrieval. ADCS 2012: 111-114 - [c28]Mike Symonds, Peter Bruza, Guido Zuccon, Laurianne Sitbon, Ian W. Turner:
Is the unigram relevance model term independent?: classifying term dependencies in query expansion. ADCS 2012: 123-127 - [c27]Teerapong Leelanupab, Guido Zuccon, Joemon M. Jose:
A comprehensive analysis of parameter settings for novelty-biased cumulative gain. CIKM 2012: 1950-1954 - [c26]Bevan Koopman, Guido Zuccon, Peter Bruza, Laurianne Sitbon, Michael Lawley:
An evaluation of corpus-driven measures of medical concept similarity for information retrieval. CIKM 2012: 2439-2442 - [c25]Guido Zuccon, Leif Azzopardi, Dell Zhang, Jun Wang:
Top-k Retrieval Using Facility Location Analysis. ECIR 2012: 305-316 - [c24]Anthony N. Nguyen, Julie Moore, Guido Zuccon, Michael Lawley, Shoni Colquist:
Classification of pathology reports for cancer registry notifications. HIC 2012: 150-156 - [c23]Guido Zuccon, Anthony N. Nguyen, Anton Bergheim, Sandra Wickman, Narelle Grayson:
The impact of OCR accuracy on automated cancer classification of pathology reports. HIC 2012: 250-256 - [c22]Bevan Koopman, Guido Zuccon, Anthony N. Nguyen, Deanne Vickers, Luke Butt, Peter Bruza:
Exploiting SNOMED CT Concepts & Relationships for Clinical Information Retrieval: Australian e-Health Research Centre and Queensland University of Technology at the TREC 2012 Medical Track. TREC 2012 - [c21]Mike Symonds, Guido Zuccon, Bevan Koopman, Peter Bruza:
QUT_Para at TREC 2012 Web Track: Word Associations for Retrieving Web Documents. TREC 2012 - 2011
- [c20]Guido Zuccon, Leif Azzopardi, Keith van Rijsbergen:
Back to the Roots: Mean-Variance Analysis of Relevance Estimations. ECIR 2011: 716-720 - [c19]Guido Zuccon, Leif Azzopardi, C. J. van Rijsbergen:
An Analysis of Ranking Principles and Retrieval Strategies. ICTIR 2011: 151-163 - [c18]Teerapong Leelanupab, Guido Zuccon, Joemon M. Jose:
A Query-Basis Approach to Parametrizing Novelty-Biased Cumulative Gain. ICTIR 2011: 327-331 - [c17]Yashar Moshfeghi, Guido Zuccon, Joemon M. Jose:
Using Emotion to Diversify Document Rankings. ICTIR 2011: 337-341 - [c16]Guido Zuccon, Benjamin Piwowarski, Leif Azzopardi:
On the use of Complex Numbers in Quantum Models for Information Retrieval. ICTIR 2011: 346-350 - [c15]Guido Zuccon, Leif Azzopardi, Enrico Gasco:
Investigating Subspace Distances in Semantic Spaces. IIR 2011 - [c14]Guido Zuccon, Leif Azzopardi, C. J. van Rijsbergen:
The interactive PRP for diversifying document rankings. SIGIR 2011: 1227-1228 - [c13]Stewart Whiting, Jesus A. Rodriguez Perez, Guido Zuccon, Teerapong Leelanupab, Joemon M. Jose:
University of Glasgow (qirdcsuog) at TREC Crowdsourcing 2011: TurkRank-Network-based Worker Ranking in Crowdsourcing. TREC 2011 - 2010
- [c12]Dawei Song, Mounia Lalmas, Keith van Rijsbergen, Ingo Frommholz, Benjamin Piwowarski, Jun Wang, Peng Zhang, Guido Zuccon, Peter Bruza, Sachi Arafat, Leif Azzopardi, Emanuele Di Buccio, Alvaro Francisco Huertas-Rosero, Yuexian Hou, Massimo Melucci, Stefan M. Rüger:
How Quantum Theory Is Developing the Field of Information Retrieval. AAAI Fall Symposium: Quantum Informatics for Cognitive, Social, and Semantic Processes 2010 - [c11]Teerapong Leelanupab, Guido Zuccon, Joemon M. Jose:
When Two Is Better Than One: A Study of Ranking Paradigms and Their Integrations for Subtopic Retrieval. AIRS 2010: 162-172 - [c10]Guido Zuccon, Leif Azzopardi:
Using the Quantum Probability Ranking Principle to Rank Interdependent Documents. ECIR 2010: 357-369 - [c9]Guido Zuccon, Leif Azzopardi:
Developing the Quantum Probability Ranking Principle. IIR 2010: 21-22 - [c8]Guido Zuccon, Leif Azzopardi, Claudia Hauff, Keith van Rijsbergen:
Estimating interference in the QPRP for subtopic retrieval. SIGIR 2010: 741-742 - [c7]Guido Zuccon, Leif Azzopardi, Keith van Rijsbergen:
Has portfolio theory got any principles? SIGIR 2010: 755-756 - [p1]Teerapong Leelanupab, Guido Zuccon, Joemon M. Jose:
Revisiting Sub-topic Retrieval in the ImageCLEF 2009 Photo Retrieval Task. ImageCLEF 2010: 277-294
2000 – 2009
- 2009
- [c6]Teerapong Leelanupab, Guido Zuccon, Anuj Goyal, Martin Halvey, P. Punitha, Joemon M. Jose:
University of Glasgow at ImageCLEFPhoto 2009: Optimising Similarity and Diversity in Image Retrieval. CLEF (2) 2009: 133-141 - [c5]Guido Zuccon, Teerapong Leelanupab, Anuj Goyal, Martin Halvey, P. Punitha, Joemon M. Jose:
The University of Glasgow at ImageCLEFPhoto 2009. CLEF (Working Notes) 2009 - [c4]Guido Zuccon, Leif Azzopardi, Keith van Rijsbergen:
The Quantum Probability Ranking Principle for Information Retrieval. ICTIR 2009: 232-240 - [c3]Guido Zuccon, Leif Azzopardi, C. J. van Rijsbergen:
Semantic Spaces: Measuring the Distance between Different Subspaces. QI 2009: 225-236 - [c2]Guido Zuccon, Leif Azzopardi, C. J. van Rijsbergen:
Revisiting logical imaging for information retrieval. SIGIR 2009: 766-767 - 2008
- [c1]Guido Zuccon, Leif Azzopardi, C. J. van Rijsbergen:
A Formalization of Logical Imaging for Information Retrieval Using Quantum Theory. DEXA Workshops 2008: 3-8
Coauthor Index
Mahsa Baktash
aka: Mahsa Baktashmotlagh
aka: Mahsa Baktashmotlagh
[c208] [c207] [c206] [c201] [i60] [i59] [i58] [i56] [i55] [i51] [i50] [i49] [i48] [i46] [j24] [c195] [c194] [c189] [c186] [c185] [c180] [i43] [i42] [i35] [i33] [i31] [i30] [j21] [c177] [c166] [c163] [c159] [i22] [i19] [i15] [i12] [i10] [j20] [j19] [c156] [c142] [c139] [i8] [c135] [c134] [c130] [c129] [c128] [j16] [c125] [c124] [c122] [c119] [c114] [c113] [j15] [j13] [j12] [c109] [c106] [c104] [c100] [j9] [c97] [c95] [c93] [c88] [c87] [c86] [c85] [e4] [j8] [c82] [c71] [c68] [j5] [c65] [c62] [c56] [j3] [c53] [c52] [c50] [c49] [c46] [c45] [c44] [c43] [c41] [c39] [c36] [c35] [c32] [c31] [c30] [c29] [c26] [c22] [c21]
João R. M. Palotti
aka: João Rafael De Moura Palotti
aka: João Rafael De Moura Palotti
C. J. van Rijsbergen
aka: Keith van Rijsbergen
aka: Keith van Rijsbergen
[c207] [c202] [i59] [i50] [i48] [c190] [c189] [c185] [i43] [i39] [i35] [i29] [j21] [c177] [c168] [c167] [c166] [c160] [c159] [i22] [i15] [i14] [i12] [j20] [c155] [c149] [c141] [c140] [i6] [i5] [i4] [c135] [c134] [c132] [c129] [c128] [c126] [c121] [c118] [c117] [c113] [c110] [c105] [c104] [c101] [c98] [c97] [c93] [c87] [c84] [c69]
[c207] [c206] [c205] [c204] [c203] [c201] [c200] [c199] [i60] [i59] [i55] [i54] [i53] [i52] [i51] [i50] [i49] [i48] [i47] [i46] [i45] [j24] [c195] [c192] [c190] [c188] [c183] [c182] [i41] [i40] [i39] [i38] [i32] [i31] [i30] [j22] [c178] [c175] [c169] [c165] [c164] [c162] [c160] [c158] [i27] [i25] [i24] [i23] [i20] [i18] [i10] [c153] [c151] [c150] [c148] [c147] [c144] [c143] [i9] [i8] [i7] [i3] [c133]
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