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2020 – today
- 2024
[j16]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. Int. J. Digit. Libr. 25(4): 569-584 (2024)- [c81]Aaron Nicolson, Jinghui Liu, Jason Dowling, Anthony N. Nguyen, Bevan Koopman:
e-Health CSIRO at RRG24: Entropy-Augmented Self-Critical Sequence Training for Radiology Report Generation. BioNLP@ACL 2024: 99-104 - [c80]Jinghui Liu, Aaron Nicolson, Jason Dowling, Bevan Koopman, Anthony N. Nguyen:
e-Health CSIRO at "Discharge Me!" 2024: Generating Discharge Summary Sections with Fine-tuned Language Models. BioNLP@ACL 2024: 675-684 - [c79]Xinyu Mao
, Bevan Koopman, Guido Zuccon:
A Reproducibility Study of Goldilocks: Just-Right Tuning of BERT for TAR. ECIR (4) 2024: 132-146 - [c78]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 - [c77]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. EMNLP 2024: 4375-4391 - [c76]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 - [c75]Xinyu Mao, Shengyao Zhuang, Bevan Koopman, Guido Zuccon:
Dense Retrieval with Continuous Explicit Feedback for Systematic Review Screening Prioritisation. SIGIR 2024: 2357-2362 - [i29]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) - [i28]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) - [i27]Xinyu Mao, Bevan Koopman, Guido Zuccon:
A Reproducibility Study of Goldilocks: Just-Right Tuning of BERT for TAR. CoRR abs/2401.08104 (2024) - [i26]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) - [i25]Shuai Wang, Shengyao Zhuang, Bevan Koopman, Guido Zuccon:
ReSLLM: Large Language Models are Strong Resource Selectors for Federated Search. CoRR abs/2401.17645 (2024) - [i24]Shengyao Zhuang, Bevan Koopman, Xiaoran Chu, Guido Zuccon:
Understanding and Mitigating the Threat of Vec2Text to Dense Retrieval Systems. CoRR abs/2402.12784 (2024) - [i23]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) - [i22]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) - [i21]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) - [i20]Aaron Nicolson, Shengyao Zhuang, Jason Dowling, Bevan Koopman:
The Impact of Auxiliary Patient Data on Automated Chest X-Ray Report Generation and How to Incorporate It. CoRR abs/2406.13181 (2024) - [i19]Xinyu Mao, Shengyao Zhuang, Bevan Koopman, Guido Zuccon:
Dense Retrieval with Continuous Explicit Feedback for Systematic Review Screening Prioritisation. CoRR abs/2407.00635 (2024) - [i18]Jinghui Liu, Aaron Nicolson, Jason Dowling, Bevan Koopman, Anthony N. Nguyen:
e-Health CSIRO at "Discharge Me!" 2024: Generating Discharge Summary Sections with Fine-tuned Language Models. CoRR abs/2407.02723 (2024) - [i17]Aaron Nicolson, Jinghui Liu, Jason Dowling, Anthony N. Nguyen, Bevan Koopman:
e-Health CSIRO at RRG24: Entropy-Augmented Self-Critical Sequence Training for Radiology Report Generation. CoRR abs/2408.03500 (2024) - [i16]Shengyao Zhuang, Bevan Koopman, Guido Zuccon:
Does Vec2Text Pose a New Corpus Poisoning Threat? CoRR abs/2410.06628 (2024) - 2023
- [j15]Aaron Nicolson, Jason Dowling, Bevan Koopman:
Improving chest X-ray report generation by leveraging warm starting. Artif. Intell. Medicine 144: 102633 (2023) - [j14]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) - [c74]Filip Rusak, Bevan Koopman, Nathan J. Brown, Kevin Chu, Jinghui Liu, Anthony N. Nguyen:
Catching Misdiagnosed Limb Fractures in the Emergency Department Using Cross-institution Transfer Learning. ALTA 2023: 78-87 - [c73]Aaron Nicolson, Jason Dowling, Bevan Koopman:
e-Health CSIRO at RadSum23: Adapting a Chest X-Ray Report Generator to Multimodal Radiology Report Summarisation. BioNLP@ACL 2023: 545-549 - [c72]Aaron Nicolson, Jason Dowling, Bevan Koopman:
A Concise Model for Medical Image Captioning. CLEF (Working Notes) 2023: 1611-1619 - [c71]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 - [c70]Bevan Koopman, Guido Zuccon:
Dr ChatGPT tell me what I want to hear: How different prompts impact health answer correctness. EMNLP 2023: 15012-15022 - [c69]Shuai Wang, Harrisen Scells, Bevan Koopman, Guido Zuccon:
Can ChatGPT Write a Good Boolean Query for Systematic Review Literature Search? SIGIR 2023: 1426-1436 - [c68]Guido Zuccon, Bevan Koopman, Razia Shaik:
ChatGPT Hallucinates when Attributing Answers. SIGIR-AP 2023: 46-51 - [c67]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 - [c66]Hang Li, Bevan Koopman, Ahmed Mourad, Guido Zuccon:
AgAsk: A Conversational Search Agent for Answering Agricultural Questions. WSDM 2023: 1140-1143 - [i15]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) - [i14]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) - [i13]Aaron Nicolson, Jason Dowling, Bevan Koopman:
Longitudinal Data and a Semantic Similarity Reward for Chest X-Ray Report Generation. CoRR abs/2307.09758 (2023) - [i12]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) - [i11]Guido Zuccon, Bevan Koopman, Razia Shaik:
ChatGPT Hallucinates when Attributing Answers. CoRR abs/2309.09401 (2023) - [i10]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) - [i9]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) - 2022
- [j13]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) - [c65]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 - [c64]Aaron Nicolson, Jason Dowling, Bevan Koopman:
ImageCLEF 2021 Best of Labs: The Curious Case of Caption Generation for Medical Images. CLEF 2022: 190-203 - [c63]Léo Lebrat, Aaron Nicolson, Rodrigo Santa Cruz, Gregg Belous, Bevan Koopman, Jason Dowling:
CSIRO at ImageCLEFmedical Caption 2022. CLEF (Working Notes) 2022: 1455-1473 - [c62]Bowen Xin, Hang Min, Ashley G. Gillman, Bevan Koopman, Jason Dowling, Aaron Nicolson:
CSIRO at the ImageCLEFmedical 2022 Tuberculosis Caverns Detection Challenge: A 2D and 3D Deep Learning Detection Network Approach. CLEF (Working Notes) 2022: 1626-1640 - [c61]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 - [c60]Duy-Hoa Ngo, Bevan Koopman:
Self-learning ontological concept representation for searching and matching tasks. OM@ISWC 2022: 73-78 - [c59]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 - [c58]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 - [i8]Duy-Hoa Ngo, Madonna Kemp, Donna Truran, Bevan Koopman, Alejandro Metke-Jimenez:
Semantic Search for Large Scale Clinical Ontologies. CoRR abs/2201.00118 (2022) - [i7]Aaron Nicolson, Jason Dowling, Bevan Koopman:
Improving Chest X-Ray Report Generation by Leveraging Warm-Starting. CoRR abs/2201.09405 (2022) - [i6]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) - [i5]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) - [i4]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) - [i3]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) - [i2]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
- [j12]Harrisen Scells, Guido Zuccon, Bevan Koopman:
A comparison of automatic Boolean query formulation for systematic reviews. Inf. Retr. J. 24(1): 3-28 (2021) - [j11]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) - [c57]Bevan Koopman, Guido Zuccon:
Cohort-based Clinical Trial Retrieval. ADCS 2021: 3:1-3:9 - [c56]Duy-Hoa Ngo, Madonna Kemp, Donna L. Truran, Bevan Koopman, Alejandro Metke-Jimenez:
Semantic Search for Large Scale Clinical Ontologies. AMIA 2021 - [c55]Aaron Nicolson, Jason Dowling, Bevan Koopman:
AEHRC CSIRO at ImageCLEFmed Caption 2021. CLEF (Working Notes) 2021: 1317-1328 - [c54]Bevan Koopman, Tracey Wright, Natacha Omer, Veronica McCabe, Guido Zuccon:
Precision Medicine Search for Paediatric Oncology. SIGIR 2021: 2536-2540 - [c53]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 - [i1]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) - 2020
- [c52]Harrisen Scells, Guido Zuccon, Bevan Koopman, Justin Clark:
A Computational Approach for Objectively Derived Systematic Review Search Strategies. ECIR (1) 2020: 385-398 - [c51]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 - [c50]Sebastian Cross, Hang Li, Arvin Zhuang, Ahmed Mourad, Guido Zuccon, Bevan Koopman:
IELAB for TREC Conversational Assistance Track (CAsT) 2020. TREC 2020 - [c49]Harrisen Scells, Guido Zuccon, Bevan Koopman, Justin Clark:
Automatic Boolean Query Formulation for Systematic Review Literature Search. WWW 2020: 1071-1081 - [c48]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
- [j10]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) - [c47]Jimmy, Guido Zuccon, Bevan Koopman, Gianluca Demartini:
Health Cards to Assist Decision Making in Consumer Health Search. AMIA 2019 - [c46]Anton H. van der Vegt, Guido Zuccon, Bevan Koopman:
Learning Inter-Sentence, Disorder-Centric, Biomedical Relationships from Medical Literature. AMIA 2019 - [c45]Jimmy, Guido Zuccon, Bevan Koopman, Gianluca Demartini:
Health Card Retrieval for Consumer Health Search: An Empirical Investigation of Methods. CIKM 2019: 2405-2408 - [c44]Jimmy, Guido Zuccon, Bevan Koopman, Gianluca Demartini:
Health Cards for Consumer Health Search. SIGIR 2019: 35-44 - [c43]Bevan Koopman, Guido Zuccon:
WSDM 2019 Tutorial on Health Search (HS2019): A Full-Day from Consumers to Clinicians. WSDM 2019: 838-839 - [c42]Harrisen Scells, Guido Zuccon, Bevan Koopman:
Automatic Boolean Query Refinement for Systematic Review Literature Search. WWW 2019: 1646-1656 - 2018
- [j9]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) - [j8]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) - [j7]Bevan Koopman, Jack Russell, Guido Zuccon:
Task-oriented search for evidence-based medicine. Int. J. Digit. Libr. 19(2-3): 217-229 (2018) - [c41]Bevan Koopman, Anthony N. Nguyen, Danica Cossio, Mary-Jane Courage, Gary Francois:
Extracting Cancer Mortality Statistics from Free-text Death Certificates: A View from the Trenches. ADCS 2018: 6:1-6:4 - [c40]Anthony N. Nguyen, Donna L. Truran, Madonna Kemp, Bevan Koopman, David Conlan, John O'Dwyer, Ming Zhang, Sarvnaz Karimi, Hamed Hassanzadeh, Michael Lawley, Damian J. Green:
Computer-Assisted Diagnostic Coding: Effectiveness of an NLP-based approach using SNOMED CT to ICD-10 mappings. AMIA 2018 - [c39]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 - [c38]Jimmy, Guido Zuccon, Bevan Koopman:
Choices in Knowledge-Base Retrieval for Consumer Health Search. ECIR 2018: 72-85 - [c37]Harrisen Scells, Leif Azzopardi, Guido Zuccon, Bevan Koopman:
Query Variation Performance Prediction for Systematic Reviews. SIGIR 2018: 1089-1092 - [c36]Guido Zuccon, Bevan Koopman:
SIGIR 2018 Tutorial on Health Search (HS2018): A Full-day from Consumers to Clinicians. SIGIR 2018: 1391-1394 - 2017
- [j6]Bevan Koopman, Guido Zuccon, Peter Bruza:
What makes an effective clinical query and querier? J. Assoc. Inf. Sci. Technol. 68(11): 2557-2571 (2017) - [c35]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 - [c34]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 - [c33]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 - [c32]Bevan Koopman, Liam Cripwell, Guido Zuccon:
Generating Clinical Queries from Patient Narratives: A Comparison between Machines and Humans. SIGIR 2017: 853-856 - [c31]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 - [c30]Bevan Koopman, Guido Zuccon, Jack Russell:
A Task-oriented Search Engine for Evidence-based Medicine. SIGIR 2017: 1329-1332 - [c29]Guido Zuccon, Bevan Koopman:
SIGIR 2017 Tutorial on Health Search (HS2017): A Full-day from Consumers to Clinicians. SIGIR 2017: 1415-1418 - [e1]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
- [j5]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) - [c28]Hamed Hassanzadeh, Anthony N. Nguyen, Bevan Koopman:
Evaluation of Medical Concept Annotation Systems on Clinical Records. ALTA 2016: 15-24 - [c27]Jimmy, Guido Zuccon, Bevan Koopman:
Boosting Titles does not Generally Improve Retrieval Effectiveness. ADCS 2016: 25-32 - [c26]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 - [c25]Bevan Koopman, Guido Zuccon:
A Test Collection for Matching Patients to Clinical Trials. SIGIR 2016: 669-672 - 2015
- [j4]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) - [j3]Bevan Koopman, Sarvnaz Karimi, Anthony N. Nguyen, Rhydwyn McGuire, David Muscatello, Madonna Kemp, Donna Truran, Ming Zhang, Sarah Thackway:
Automatic classification of diseases from free-text death certificates for real-time surveillance. BMC Medical Informatics Decis. Mak. 15: 53 (2015) - [c24]Guido Zuccon, Bevan Koopman, Peter Bruza, Leif Azzopardi:
Integrating and Evaluating Neural Word Embeddings in Information Retrieval. ADCS 2015: 12:1-12:8 - [c23]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 - [c22]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 - 2014
- [j2]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) - [j1]Bevan Koopman:
Semantic Search as Inference: Applications in Health Informatics. SIGIR Forum 48(2): 116-117 (2014) - [c21]Bevan Koopman, Guido Zuccon:
Document Timespan Normalisation and Understanding Temporality for Clinical Records Search. ADCS 2014: 85 - [c20]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 - [c19]Guido Zuccon, Bevan Koopman, Peter Bruza:
Exploiting Inference from Semantic Annotations for Information Retrieval: Reflections From Medical IR. ESAIR 2014: 43-45 - [c18]Lance De Vine, Guido Zuccon, Bevan Koopman, Laurianne Sitbon, Peter Bruza:
Medical Semantic Similarity with a Neural Language Model. CIKM 2014: 1819-1822 - [c17]Bevan Koopman, Guido Zuccon:
Why Assessing Relevance in Medical IR is Demanding. MedIR@SIGIR 2014: 16-19 - [c16]Guido Zuccon, Bevan Koopman:
Integrating Understandability in the Evaluation of Consumer Health Search Engines. MedIR@SIGIR 2014: 32-35 - [c15]Bevan Koopman, Guido Zuccon:
Understanding negation and family history to improve clinical information retrieval. SIGIR 2014: 971-974 - [c14]Bevan Koopman, Guido Zuccon:
Relevation!: an open source system for information retrieval relevance assessment}. SIGIR 2014: 1243-1244 - 2013
- [c13]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 - [c12]Michael Symonds, Guido Zuccon, Bevan Koopman, Peter Bruza, Laurianne Sitbon:
Term associations in query expansion: a structural linguistic perspective. CIKM 2013: 1189-1192 - [c11]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 - [c10]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 - [c9]Peter Wittek, Bevan Koopman, Guido Zuccon, Sándor Darányi:
Combining Word Semantics within Complex Hilbert Space for Information Retrieval. QI 2013: 160-171 - 2012
- [c8]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 - [c7]Bevan Koopman, Guido Zuccon, Peter Bruza, Laurianne Sitbon, Michael Lawley:
Graph-based concept weighting for medical information retrieval. ADCS 2012: 80-87 - [c6]Guido Zuccon, Bevan Koopman, Anthony N. Nguyen, Deanne Vickers, Luke Butt:
Exploiting medical hierarchies for concept-based information retrieval. ADCS 2012: 111-114 - [c5]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 - [c4]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 - [c3]Mike Symonds, Guido Zuccon, Bevan Koopman, Peter Bruza:
QUT_Para at TREC 2012 Web Track: Word Associations for Retrieving Web Documents. TREC 2012 - 2011
- [c2]Bevan Koopman, Peter Bruza, Laurianne Sitbon, Michael Lawley:
Evaluating medical information retrieval. SIGIR 2011: 1139-1140 - [c1]Bevan Koopman, Michael Lawley, Peter Bruza, Laurianne Sitbon:
AEHRC & QUT at TREC 2011 Medical Track: A Concept-Based Information Retrieval Approach. TREC 2011
Coauthor Index
[j16] [c79] [c78] [c77] [c76] [c75] [i29] [i28] [i27] [i26] [i25] [i24] [i23] [i22] [i21] [i19] [i16] [j14] [c71] [c70] [c69] [c68] [c67] [c66] [i15] [i14] [i12] [i11] [i10] [i9] [j13] [c65] [c61] [c59] [c58] [i6] [i5] [i4] [i3] [i2] [j12] [j11] [c57] [c54] [c53] [i1] [c52] [c51] [c50] [c49] [c48] [j10] [c47] [c46] [c45] [c44] [c43] [c42] [j9] [j8] [j7] [c39] [c38] [c37] [c36] [j6] [c35] [c34] [c33] [c32] [c31] [c30] [c29] [e1] [j5] [c27] [c26] [c25] [j4] [c24] [c23] [c22] [j2] [c21] [c20] [c19] [c18] [c17] [c16] [c15] [c14] [c13] [c12] [c11] [c10] [c9] [c8] [c7] [c6] [c5] [c4] [c3]
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