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<html>
<head>
<title>Bevan Koopman's Homepage</title>
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<body>
<div id="main">
<div class="header">
<h1>Bevan R. Koopman</h1>
<h2>Researcher in Search & Language Technologies</h2>
</div>
<div id="main">
<div class="sidebar">
<div class="sidebaritem" id="photo">
<img src="img/bevan_koopman-sketch.jpg" alt="Bevan Koopman"><br>
</div>
<div class="sidebaritem" style="text-align: center">
<a href="http://twitter.com/bevan_koopman"><img class="socialmediabadge" src="img/twitter2.png" alt="Twitter"></a>
<a href="http://au.linkedin.com/in/bevankoopman"><img class="socialmediabadge" src="img/linkedin2.png" alt="LinkedIn"></a>
<a href="http://github.com/bevankoopman"><img class="socialmediabadge" src="img/github2.png" alt="Github"></a>
</div>
</div>
<div class="content">
<h2 class="content-subhead">About Me</h2>
<p>
I'm a researcher focused on search and language technologies. I lead the Health Search team at the <a href="http://aehrc.com/">Australian e-Health Research Centre</a>, <a href="http://csiro.au">CSIRO (Commonwealth Scientific and Industrial Research Organisation)</a> and I'm an Associate Professor in Language Technologies at the <a href="http://itee.uq.edu.au">School of Information Technology and Electrical Engineering</a>, <a href="http://www.uq.edu.au">Univeristy of Queensland</a>.
</p>
<p><strong>At its core, my research has been about helping people find relevant and reliable health information to make health related decisions.</strong></p>
<p>From a <strong>clinical perspective</strong> then, my research is to tackle problems where people need to find answers and make clinical decisions in the face of overwhelming amounts of typically unstructured data. So that might be in evidence-based medicine, where clinicians need to search through vast amounts of literature and clinical trials to find a targeted treatment for a specific cancer. It can be automating the processing of matching and recruiting a patient to a clinical trials. </p>
<p>From a <strong>technical perspective</strong>, the key challenges here are 1) how to build models search through unstructured natural language; 2) understanding the semantics of someones query rather than just matching keywords; 3) how to inject medical domain knowledge into an AI model; 4) putting the human searcher in the loop so they can bring their domain knowledge to guide the model to relevant information; 5) the underlying techniques nowadays being training specific deep learning based ranking models.</p>
<h2 class="content-subhead">Contact</h2>
<p>
<a href="http://aehrc.com/">Australian e-Health Research Centre</a><br>
Lvl 7, STARS Hospital, 296 Herston Rd, Herston, Queensland 4029, AUSTRALIA.<br>
(<a href='https://goo.gl/maps/SCTWbHY1QpJKFpAr5'>Location on Google Maps</a>)<br>
<!-- Phone: +61 7 3253 3600<br> -->
Email: <a href="mailto:[email protected]" target="_top">[email protected]</a><br>
</p>
<h2 class="content-subhead">Publications</h2>
<div class="scholar">
<a href="http://scholar.google.com.au/citations?user=twCn-tYAAAAJ">Google Scholar Profile</a>
</div>
<h3>2024</h3>
<ul class=publications>
<li><strong>B. Koopman</strong> and G. Zuccon. Dr chatgpt, tell me what i want to hear: How prompt knowledge impacts health answer correctness. In EMNLP, December 2023..<span class="long">Long paper</span></li>
<li>J. Liu, A. Nicolson, J. Dowling, <strong>B. Koopman</strong>, and A. Nguyen. e-health csiro at” discharge me!” 2024: Generating discharge summary sections with fine-tuned language models. arXiv preprint arXiv:2407.02723, 2024.<span class="long">Long paper</span></li>
<li>X. Mao, <strong>B. Koopman</strong>, and G. Zuccon. A reproducibility study of goldilocks: Just-right tuning of bert for tar. In European Conference on Information Retrieval, pages 132–146. Springer, Cham, 2024.<span class="long">Long paper</span></li>
<li>X. Mao, S. Zhuang, <strong>B. Koopman</strong>, and G. Zuccon. Dense retrieval with continuous explicit feedback for systematic review screening prioritisation. In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 2357–2362, 2024.<span class="short">Short paper</span></li>
<li>A. Nicolson, J. Liu, J. Dowling, A. Nguyen, and <strong>B. Koopman</strong>. e-health csiro at rrg24: Entropy-augmented self-critical sequence training for radiology report generation. arXiv preprint arXiv:2408.03500, 2024.<span class="long">Long paper</span></li>
<li>A. Nicolson, S. Zhuang, J. Dowling, and <strong>B. Koopman</strong>. The impact of auxiliary patient data on automated chest x-ray report generation and how to incorporate it. arXiv preprint arXiv:2406.13181, 2024.<span class="long">Long paper</span></li>
<li>F. Schlatt, M. Fr ̈obe, H. Scells, S. Zhuang, <strong>B. Koopman</strong>, G. Zuccon, B. Stein, M. Potthast, and M. Hagen. Set-encoder: Permutation-invariant inter-passage attention for listwise passage re-ranking with cross-encoders. arXiv preprint arXiv:2404.06912, 2024.<span class="long">Long paper</span></li>
<li>F. Schlatt, M. Fr ̈obe, H. Scells, S. Zhuang, <strong>B. Koopman</strong>, G. Zuccon, B. Stein, M. Potthast, and M. Hagen. A systematic investigation of distilling large language models into cross-encoders for passage re-ranking. arXiv preprint arXiv:2405.07920, 2024.<span class="long">Long paper</span></li>
<li>S. Wang, H. Scells, S. Zhuang, M. Potthast, <strong>B. Koopman</strong>, and G. Zuccon. Zero-shot generative large language models for systematic review screening automation. In European Conference on Information Retrieval, pages 403–420. Springer, Cham, 2024.<span class="long">Long paper</span></li>
<li>S. Wang, S. Zhuang, <strong>B. Koopman</strong>, and G. Zuccon. Resllm: Large language models are strong resource selectors for federated search. arXiv preprint arXiv:2401.17645, 2024.<span class="long">Long paper</span></li>
<li>C. Yu, H. Li, A. Mourad, <strong>B. Koopman</strong>, and G. Zuccon. TPRF: A transformer-based pseudo-relevance feedback model for efficient and effective retrieval. arXiv preprint arXiv:2401.13509, 2024.<span class="long">Long paper</span></li>
<li>S. Zhuang, <strong>B. Koopman</strong>, X. Chu, and G. Zuccon. Understanding and mitigating the threat of vec2text to dense retrieval systems. arXiv preprint arXiv:2402.12784, 2024.<span class="long">Long paper</span></li>
<li>S. Zhuang, <strong>B. Koopman</strong>, and G. Zuccon. Team ielab at trec clinical trial track 2023: Enhancing clinical trial retrieval with neural rankers and large language models. arXiv preprint arXiv:2401.01566, 2024.<span class="demo">Notebook</span></li>
<li>S. Zhuang, B. Liu, <strong>B. Koopman</strong>, and G. Zuccon. Open-source large language models are strong zero-shot query likelihood models for document ranking. In EMNLP Findings, December 2023.<span class="long">Long paper</span></li>
<li>S. Zhuang, X. Ma, <strong>B. Koopman</strong>, J. Lin, and G. Zuccon. Promptreps: Prompting large language models to generate dense and sparse representations for zero-shot document retrieval. arXiv preprint arXiv:2404.18424, 2024.<span class="long">Long paper</span></li>
<li>S. Zhuang, H. Zhuang, <strong>B. Koopman</strong>, and G. Zuccon. A setwise approach for effective and highly efficient zero-shot ranking with large language models. In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 38–47, 2024.<span class="long">Long paper</span></li>
</ul>
<h3>2023</h3>
<ul class=publications>
<li><strong>B. Koopman</strong> and G. Zuccon. Dr chatgpt tell me what i want to hear: How different prompts impact health answer correctness. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 15012–15022, 2023.<span class="long">Long paper</span></li>
<li>D.-H. Ngo and <strong>B. Koopman</strong>. From free-text drug labels to structured medication terminology with bert and gpt. In AMIA Annual Symposium Proceedings, volume 2023, page 540. American Medical Informatics Association, 2023.<span class="long">Long paper</span></li>
<li>A. Nicolson, J. Dowling, and <strong>B. Koopman</strong>. A concise model for medical image captioning. In CLEF (Working Notes), pages 1611–1619, 2023.<span class="demo">Notebook</span></li>
<li>A. Nicolson, J. Dowling, and <strong>B. Koopman</strong>. e-health csiro at radsum23: Adapting a chest x-ray report generator to multimodal radiology report summarisation. In The 22nd Workshop on Biomedical Natural Language Processing and BioNLP Shared Tasks, pages 545–549, 2023.<span class="demo">Notebook</span></li>
<li>A. Nicolson, J. Dowling, and <strong>B. Koopman</strong>. Improving chest x-ray report generation by leveraging warm starting. Artificial intelligence in medicine, 144:102633, 2023.<span class="journal">Journal</span></li>
<li>A. Nicolson, J. Dowling, and <strong>B. Koopman</strong>. Longitudinal data and a semantic similarity reward for chest x-ray report generation. arXiv preprint arXiv:2307.09758, 2023.<span class="long">Long paper</span></li>
<li>F. Rusak, <strong>B. Koopman</strong>, N. J. Brown, K. Chu, J. Liu, and A. Nguyen. Catching misdiagnosed limb fractures in the emergency department using cross-institution transfer learning. In Proceedings of the 21st Annual Workshop of the Australasian Language Technology Association, pages 78–87, 2023.<span class="long">Long paper</span></li>
<li>S. Wang, H. Scells, <strong>B. Koopman</strong>, M. Potthast, and G. Zuccon. Generating natural language queries for more effective systematic review screening prioritisation. In Proceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region, pages 73–83, 2023.<span class="long">Long paper</span></li>
<li>S. Wang, H. Scells, M. Potthast, <strong>B. Koopman</strong>, and G. Zuccon. Generating Natural Language Queries for More Effective Systematic Review Screening Prioritisation. In SIGIR-AP, Sept. 2023.<span class="long">Long paper</span></li>
<li>G. Zuccon, <strong>B. Koopman</strong>, and R. Shaik. Chatgpt hallucinates when attributing answers. In Proceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region, pages 46–51, 2023.<span class="long">Long paper</span></li>
<li><strong>B. Koopman</strong>, A. Mourad, H. Li, A. v. d. Vegt, S. Zhuang, S. Gibson, Y. Dang, D. Lawrence, and G. Zuccon. <a href="papers/ijdl2022-AgAsk_end_to_end.pdf">Agask: an agent to help answer farmer's questions from scientific documents.</a> International Journal on Digital Libraries, June 2023. <span class="journal">Journal</span></li>
<li>H. Li, <strong>B. Koopman</strong>, A. Mourad, and G. Zuccon. <a href="papers/wsdm2023-agask-demo.pdf">Agask: A conversational search agent for answering agricultural questions</a>. In Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, WSDM '23, Feb 2023. <span class="short">Short paper</span></li>
<li>H. Li, A. Mourad, S. Zhuang, <strong>B. Koopman</strong>, and G. Zuccon. <a href="papers/tois2023-prf_dr.pdf">Pseudo relevance feedback with deep language models and dense retrievers: Successes and pitfalls</a>. ACM Transactions on Information Systems, 41(3):1- 40, 2023.<span class="journal">Journal</span></li>
<li>S. Wang, H. Scells, <strong>B. Koopman</strong>, and G. Zuccon. <a href="papers/sigir2023-chatgpt_sr.pdf">Can chatgpt write a good boolean query for systematic review literature search?</a> In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2023)., July 2023.<span class="long">Long paper</span></li>
</ul>
<h3>2022</h3>
<ul class=publications>
<li>L. Lebrat, A. Nicolson, R. Santa Cruz, G. Belous, <strong>B. Koopman</strong>, and J. Dowling. <a href="papers/imageclef2022-csiro_caption.pdf">CSIRO at Image-CLEFMedical caption 2022</a>. In Proceedings of the Working Notes of CLEF 2022, pages 1455-1473, Bologna, Italy, Sept. 2022. <span class="demo">Notebook</span></li>
<li>A. Nicolson, J. Dowling, and <strong>B. Koopman</strong>,. <a href="papers/imageclef2021-curious.pdf">ImageCLEF 2021 Best of Labs: The Curious Case of Caption Generation for Medical Images</a>. CLEF, volume 13390, pages 1-14. Springer, 2022.<span class="long">Long paper</span></li>
<li>A. Nicolson, J. Dowling, and <strong>B. Koopman</strong>. <a href="papers/aim2023-warmstart.pdf">Improving Chest X-Ray Report Generation by Leveraging Warm-Starting</a>. Artificial Intelligence in Medicine, Jan. 2022. <span class="journal">Journal</span></li>
<li>B. Xin, H. Min, A. G. Gillman, B. Koopman, J. Dowling, and A. Nicolson. <a href="papers/clef2022-cavern.pdf">CSIRO at the ImageCLEFmed 2022 Tuberculosis Caverns Detection Challenge: A 2D and 3D deep learning detection network approach</a>. In Proceedings of the Working Notes of CLEF 2022, pages 1626-1640, Bologna, Italy, Sept. 2022.<span class="demo">Notebook</span></li>
<li>S. Wang, H. Scells, J. Clark, <strong>B. Koopman</strong>, and G. Zuccon. <a href="papers/sigir2022-sr_seed_collection.pdf">From little things big things grow: A collection with seed studies for medical systematic review literature search</a>. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR '22, pages 3176-3186, 2022.<span class="long">Long paper</span></li>
<li>H. Scells, C. Forbes, J. Clark, <strong>B. Koopman</strong>, and G. Zuccon. <a href="papers/ictir2022-query_refine_log.pdf">The impact of query refinement on systematic review literature search: A query log analysis</a>. In International Conference on the Theory of Information Retrieval (ICTIR), 2022.<span class="long">Long paper</span></li>
<li>H. Li, A. Mourad, S. Zhuang, <strong>B. Koopman</strong>, and G. Zuccon. <a href="papers/tois2022-prf.pdf">Pseudo relevance feedback with deep language models and dense retrievers: Successes and pitfalls</a>. Transactions in Information Systems (TOIS), 2022.<span class="journal">Journal</span></li>
<li>H. Li, A. Mourad, <strong>B. Koopman</strong>, and G. Zuccon. <a href="papers/sigir2022-nprf.pdf">How does feedback signal quality impact effectiveness of pseudo relevance feedback for passage retrieval</a>. In SIGIR Conference on Research and Development in Information Retrieval, pages 2154-2158, 2022.<span class="short">Short paper</span></li>
</ul>
<h3>2021</h3>
<ul class=publications>
<li><strong>B. Koopman</strong> and G. Zuccon. <a href="papers/adcs2021-recruitment_coverage.pdf">Cohort-aware clinical trials retrieval</a>. In Australasian Document Computing Symposium (ADCS), Melbourne, Australia, 2021..<span class="long">Long paper</span></li>
<li>D.-H. Ngo, M. Kemp, D. Truran, <strong>B. Koopman</strong>, and A. Metke-Jimenez. <a href="papers/amia2021-SnomedCT_Semantic_Search.pdf">Semantic search for large scale clinical terminology</a>. In AMIA 2021 Annual Symposium, Nov 2021.<span class="long">Long paper</span></li>
<li>A. Nicolson, J. Dowling, and <strong>B. Koopman</strong>. <a href="papers/imageclefmed21-caption.pdf">AEHRC CSIRO in ImageCLEFmed caption 2021</a>. In CLEF2021 Working Notes, CEUR Workshop Proceedings, CEUR-WS. org, Bucharest, Romania, 2021.<span class="demo">Notebook</span></li>
<li><strong>B. Koopman</strong>, T. Wright, N. Omer, V. McCabe, and G. Zuccon. <a href="papers/sigir2021-oscar_demo.pdf">Precision medicine search for paediatric oncology</a>. In SIGIR, 2021.<span class="short">Short paper</span></li>
<li>S. Cross, A. Mourad, G. Zuccon, and <strong>B. Koopman</strong>. <a href="papers/www2021-symptom_checkers.pdf">Search engines vs. symptom checkers: A comparison of their effectiveness for online health advice</a>. In Proceedings of the Web Conference 2021, WWW '21, pages 206-216, 2021.<span class="long">Long paper</span></li>
</ul>
<h3>2020</h3>
<ul class=publications>
<li>H. Scells, G. Zuccon, <strong>B. Koopman</strong>. <a href="papers/irj2020-comparison.pdf">A comparison of automatic Boolean query formulation for systematic reviews</a>. Information Retrieval Journal, Oct. 2020.<span class="journal">Journal</span></li>
<li>H. Scells, G. Zuccon, <strong>B. Koopman</strong>, and J. Clark. <a href="papers/www2020-conceptual.pdf">Automatic boolean query formulation for systematic review literature search</a>. In The World Wide Web Conference, 2020.<span class="long">Long paper</span></li>
<li>A. van der Vegt, G. Zuccon, and <strong>B. Koopman</strong>. <a href="papers/jasist2020-better.pdf">Do better search engines really equate to better clinical decisions? If not, why not?</a> Journal of the Association for Information Science and Technology, 2020.<span class="journal">Journal</span></li>
<li>A. van der Vegt, G. Zuccon, <strong>B. Koopman</strong>, and A. Deacon. <a href="papers/jmla2020-timepressure.pdf">How searching under time pressure impacts clinical decision making</a>. Journal of the Medical Library Association, 108(4), 2020.<span class="journal">Journal</span></li>
<li><strong>B. Koopman</strong>, G. Zuccon, S. Chapman, Y. Dang, and D. Lawrence. <a href="papers/cair2020-AgAsk.pdf">How a conversational agent might help farmers in the field</a>. In 3rd International Workshop on Conversational Approaches to Information Retrieval (CAIR'20), Vancouver, Canada, 2020.<span class="long">Long paper</span></li>
<li> H. Scells, G. Zuccon, and <strong>B. Koopman</strong>. <a href="papers/ecir2020-clf.pdf">You can teach an old dog new tricks - rank fusion applied to coordination level matching for ranking in systematic reviews</a>. In European Conference on Information Retrieval. Springer, 2020.<span class="long">Long paper</span></li>
<li> H. Scells, G. Zuccon, <strong>B. Koopman</strong>, and J. Clark. <a href="papers/ecir2020-objective.pdf">A computational approach for objectively derived systematic review search strategies</a>. In European Conference on Information Retrieval. Springer, 2020.<span class="long">Long paper</span></li>
<li> H. Scells, G. Zuccon, M. A. Sharaf, and <strong>B. Koopman</strong>. <a href="papers/www2020-samplying.pdf">Sampling query variations for learning to rank to improve automatic boolean query generation in systematic reviews</a>. In The World Wide Web Conference, 2020.<span class="long">Long paper</span></li>
</ul>
<h3>2019</h3>
<! -- 080704 -->
<ul class=publications>
<li> Jimmy, G. Zuccon, <strong>B. Koopman</strong>, and G. Demartini. <a href="papers/cikm2019-health_card.pdf">Health card retrieval for consumer health search: An empirical investigation of methods</a>. In Proceedings of the 28th ACM International Conference on Information and Knowledge Management, pages 2405-2408, 2019.<span class="long">Long paper</span></li>
<li> H. Scells, G. Zuccon, <strong>B. Koopman</strong>, and J. Clark. <a href="https://colloquium2019.cochrane.org/abstracts/automatic-search-strategy-reformulation-interface-systematic-reviews">Automatic search strategy reformulation interface for systematic reviews</a>. In Proceedings of the Cochrane Colloquium, 2019.<span class="demo">Abstract</span></li>
<li> H. Scells, G. Zuccon, <strong>B. Koopman</strong>, and J. Clark. <a href="https://colloquium2019.cochrane.org/abstracts/visualising-systematic-review-search-strategies-assist-information-specialists">Visualising systematic review search strategies to assist information specialists</a>. In Abstracts of the 2019 Cochrane Colloquium, Santiago, Chile, 2019.<span class="long">Long paper</span></li>
<li><strong>B. Koopman</strong>, A. Nguyen, D. Cossio, M.-J. Courage, and G. Francois. <i><a href="papers/HIC2019-Death.pdf">What can we deep learn about cancer mortality?</a></i> In Health Informatics Conference (HIC), Melbourne, Australia, 2019.<span class="demo">Abstract</span></li>
<li>Jimmy, G. Zuccon, <strong>B. Koopman</strong>, and G. Demartini. <i><a href="papers/sigir2019-health_cards.pdf">Health cards for consumer health search</a></i>. In Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), Paris, France, July 2019.<span class="long">Long paper</span></li>
<li>A. van der Vegt, G. Zuccon, <strong>B. Koopman</strong>, and A. Deacon. <i><a href="papers/jmir2019-impact.pdf">Impact of a search engine on clinical decisions under time and system effectiveness constraints: Research protocol</a></i>. JMIR research protocols, 8(5), 2019.<span class="journal">Journal</span></li>
<li>Jimmy, G. Zuccon, G. Demartini, and <strong>B. Koopman</strong>. <i><a href="papers/amia2019-assist_decision.pdf">Health cards to assist decision making in consumer health search</a></i>. In American Medical Informatics Association Annual Symposium (AMIA), Chicago, USA, 2019.<span class="long">Long paper</span></li>
<li>A. H. van der Vegt, G. Zuccon, and <strong>B. Koopman</strong>. <i><a href="papers/amia2019-rel_ex.pdf">Learning inter-sentence, disorder-centric, biomedical relationships from medical literature</a></i>. In American Medical Informatics Association Annual Symposium (AMIA), Washington D.C., USA, 2019.<span class="long">Long paper</span></li>
<li>H. Scells, G. Zuccon, and <strong>B. Koopman</strong>. <i><a href="papers/scells2019refining.pdf">Automatic boolean query refinement for systematic review literature search</a></i>. In WWW Conference, San Francisco, USA, May 2019.<span class="long">Long paper</span></li>
<li><strong>B. Koopman</strong> and G. Zuccon. <i><a href="papers/wsdm2018-health_tutorial.pdf">WSDM 2019 tutorial on health search (HS2018): A full-day from consumers to clinicians</a></i>. In 12th ACM International WSDM Conference, 2019.<span class="demo">Tutorial</span></li>
</ul>
<h3>2018</h3>
<ul class=publications>
<li><strong>B. Koopman</strong>, A. Nguyen, D. Cossio, M.-J. Courage, and G. Francois. <i><a href="papers/adcs2018-death.pdf">Extracting cancer mortality statistics from free-text death certificates: A view from the trenches</a></i>. In Proceedings of the 23rd Australasian Document Computing Symposium, ADCS'18, pages 6:1-6:4, Dunedin, New Zealand.<span class="short">Short paper</span></li>
<li><strong>B. Koopman</strong>, A. Trotman, and P. Thomas, editors. <i><a href="https://dl.acm.org/citation.cfm?id=3291992">Proceedings of the 23rd Australasian Document Computing Symposium</a></i>. Association for Computing Machinery, 2018.<span class="journal">Editor</span></li>
<li>Jimmy, G. Zuccon, and <strong>B. Koopman</strong>. <i><a href="https://link.springer.com/article/10.1007%2Fs10791-018-9344-z">Payoffs and pitfalls in using knowledge-bases for consumer health search</a></i>. Information Retrieval Journal, Nov 2018.<span class="journal">Journal</span></li>
<li>Jimmy, G. Zuccon, and <strong>B. Koopman</strong>. <i><a href="papers/clef2018-kbr.pdf">QUT ielab at CLEF 2018 consumer health search task: Knowledge base retrieval for consumer health search</a></i>. In CEUR Workshop Proceedings: Working Notes of CLEF 2018: Conference and Labs of the Evaluation Forum, 2018.<span class="workshop">Workshop paper</span></li>
<li>A. Nguyen, D. Truran, M. Kemp, <strong>B. Koopman</strong>, D. Conlan, J. O'Dwyer, M. Zhang, S. Karimi, H. Hassanzadeh, M. Lawley, and D. Green. <i><a href="papers/amia-2018-nguyen.pdf">Computer-assisted diagnostic coding: Effectiveness of an NLP-based approach using SNOMED CT to ICD-10 mappings</a></i>. In American Medical Informatics Association Annual Symposium (AMIA), 2018.<span class="long">Long paper</span></li>
<li>H. Scells, L. Azzopardi, G. Zuccon, and <strong>B. Koopman</strong>. <i><a href="papers/sigir2018_qvpp.pdf">Query variation performance prediction for systematic reviews</a></i>. In Proceedings of the 41st International ACM SIGIR Conference on Research and Development in Information Retrieval, Ann Arbor, U.S.A, 2018. <span class="short">Short paper</span></li>
<li>G. Zuccon and <strong>B. Koopman</strong>. <i><a href="papers/sigir2018-health_search-tutorial.pdf">SIGIR 2018 tutorial on health search (hs2018): A full-day from consumers to clinicians</a></i>. In The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, SIGIR '18, pages 1391-1394, Ann Arbor, MI, USA, 2018.<span class="demo">Tutorial</span></li>
<li> <strong>B. Koopman</strong>, G. Zuccon, A. Nguyen, A. Bergheim, and N. Grayson. <i><a href="papers/aim2017-cinsw_fusion_archtecture.pdf">Extracting cancer mortality statistics from death certificates: A hybrid machine learning and rule-based approach for common and rare cancers</a></i>. Artificial Intelligence in Medicine, To appear, 2018.<span class="journal">Journal</span></li>
<li>Jimmy, G. Zuccon, and <strong>B. Koopman</strong>. <i><a href="papers/ecir2018_choices_in_knowledge_graph_retrieval.pdf">Choices in knowledge-base retrieval for consumer health search</a></i>. In European Conference on Information Retrieval, 2018.<span class="long">Long paper</span></li>
<li>A. van der Vegt, G. Zuccon, and <strong>B. Koopman</strong>. <i><a href="papers/jdoc201718_task_completion.pdf">A task completion framework to support single-interaction IR research</a></i>. Journal of Documentation, , 74(2):289-308, 2018.<span class="journal">Journal</span></li>
</ul>
<h3>2017</h3>
<ul class=publications>
<li><strong>B. Koopman</strong>, G. Zuccon, and M. Carman, editors. <i><a href="https://dl.acm.org/citation.cfm?id=3166072">ADCS 2017: Proceedings of the 22nd Australasian Document Computing Symposium</a></i>. Brisbane, Australia. ACM, 2017.<span class="journal">Editor</span></li>
<li>H. Scells, G. Zuccon, <strong>B. Koopman</strong>, A. Deacon, L. Azzopardi, and S. Geva. <i><a href="papers/cikm2017_clitrials_pico.pdf">Integrating the framing of clinical questions via pico into the retrieval of medical literature for systematic reviews</a></i>. In ACM International Conference on Information and Knowledge Management (CIKM), Singapore, 2017.<span class="short">Short paper</span></li>
<li>H. Scells, G. Zuccon, A. Deacon, and <strong>B. Koopman</strong>. <i><a href="papers/clef2017-tar.pdf">QUT ielab at CLEF eHealth 2017 technology assisted reviews track: Initial experiments with learning to rank</a></i>. Working Notes of CLEF 2017: Conference and Labs of the Evaluation Forum, volume 1866, pages Paper-98. CEUR Workshop Proceedings, 2017.<span class="long">Long paper</span></li>
<li><strong>B. Koopman</strong>, G. Zuccon, and P. Bruza. <i><a href="papers/jasist-clinical_trials_query_generation.pdf">What makes an effective clinical query and querier?</a></i> Journal of the Association for Information Science and Technology, 68(11):2557-2571, 2017.<span class="journal">Journal</span></li>
<li><strong>B. Koopman</strong>, L. Cripwell, and G. Zuccon. <i><a href="papers/sigir2017-querygeneration.pdf">Generating clinical queries from patient narratives: A comparison between machines and humans</a></i>. In SIGIR, Tokyo, Japan, August 2017.<span class="short">Short paper</span></li>
<li><strong>B. Koopman</strong>, G. Zuccon, and J. Russell. <i><a href="papers/sigir2017-demo-task_oriented_ebm.pdf">A task-oriented search engine for evidence-based medicine</a></i>. In SIGIR demo, Tokyo, Japan, August 2017.<span class="demo">Demo paper</span></li>
<li>H. Scells, G. Zuccon, <strong>B. Koopman</strong>, A. Deacon, and S. Geva. <i><a href="papers/sigir2017_sysrev_collection.pdf">A test collection for evaluating retrieval of studies for inclusion in systematic reviews</a></i>. In SIGIR, Tokyo, Japan, August 2017.<span class="short">Short paper</span></li>
<li>G. Zuccon and <strong>B. Koopman</strong>. <i><a href="papers/sigir2017-health_tutorial.pdf">SIGIR 2017 tutorial on health search (HS2017): A full-day from consumers to clinicians</a>.</i> SIGIR Tutorial, Tokyo, Japan, August 2017. <span class="demo">Tutorial</span></li>
<li>B. Koopman, J. Russell, and G. Zuccon. <i><a href="https://link.springer.com/article/10.1007%2Fs00799-017-0209-7">Task-oriented search for evidence-based medicine</a></i>. International Journal of Digital Libraries, 2017.<span class="journal">Journal</span></li>
</ul>
<h3>2016</h3>
<ul class=publications>
<li>Jimmy, G. Zuccon, and <strong>B. Koopman</strong>. <i><a href="papers/adcs2016-titles.pdf">Boosting titles does not generally improve retrieval effectiveness</a></i>. In Proceedings of the 21st Australasian Document Computing Symposium, ADCS '16, pages 25-32, Melbourne, Australia, 2016.
<span class="long">Long paper</span></li>
<li>H. Hassanzadeh, A. Nguyen, and <strong>B. Koopman</strong>. <i><a href="papers/alta2016-concept_annotation.pdf">Evaluation of medical concept annotation systems on clinical records</a></i>. In Proceedings of the Australasian Language Technology Association Workshop 2016, pages 15-24, Melbourne, Australia, December 2016.<span class="long">Long paper</span></li>
<li>A. Lipani, G. Zuccon, M. Lupu, <strong>B. Koopman</strong>, and A. Hanbury. <i><a href="papers/ictir2016-impact-fixed-cost.pdf">The impact of fixed-cost pooling strategies on test collection bias</a></i>. In International Conference on the Theory of Information Retrieval (ICTIR), Newark, USA, September 2016.<span class="short">Short paper</span></li>
<li><strong>B. Koopman</strong> and G. Zuccon. <i><a href="papers/sigir2016_clinicaltrials_collection.pdf">A test collection for matching patients to clinical trials</a></i>. In Proceedings of the 39th annual international ACM SIGIR conference on research and development in information retrieval, Pisa, July 2016. <span class="short">Short paper</span></li>
</ul>
<h3>2015</h3>
<ul class=publications>
<li>G. Zuccon, <strong>B. Koopman</strong>, P. Bruza, and L. Azzopardi. <i><a href="http://dl.acm.org/citation.cfm?id=2838936">Integrating and evaluating neural word embeddings in information retrieval</a></i>. In Australasian Document Computing Symposium (ADCS), Sydney, Australia, December 2015. <span class="long">Long paper</span></li>
<li><strong>B. Koopman</strong>, G. Zuccon, P. Bruza, L. Sitbon, and M. Lawley. <i><a href="papers/jir2015-gin.pdf">Information retrieval as semantic inference: A graph inference model applied to medical search</a></i>. Information Retrieval, 19(1):6-37, 2015.<span class="journal">Journal</span></li>
<li><strong>B. Koopman</strong>, G. Zuccon, A. Nguyen, A. Bergheim, and N. Grayson. <i><a href="papers/jmi2014-CancerCascadeClassification.pdf">Automatic ICD-10 classification of cancers from free-text death certificates</a></i>. Journal of Medical Informatics, 84(11):956-965, 2015. <span class="journal">Journal</span></li>
<li><strong>B. Koopman</strong>, G. Zuccon, A. Wagholikar, K. Chu, J. O'Dwyer, A. Nguyen, and G. Keijzers. <i><a href="papers/amia-edradiology.pdf">Automated reconciliation of radiology reports and discharge summaries</a></i>. In American Medical Informatics Association Annual Symposium (AMIA), November 2015. <span class="long">Long paper</span></li>
<li><strong>B. Koopman</strong>, S. Karimi, A. Nguyen, R. McGuire, D. Muscatello, M. Kemp, D. Truran, M. Zhang, and S. Thackway. <i><a href="papers/MoH-DiseaseSurveillance-BMC.pdf">Automatic classification of diseases from free-text death certificates for real-time surveillance</a></i>. BMC Medicial Informatics and Decision Making, 15(1):1-10, 2015.<span class="journal">Journal</span></li>
<li>G. Zuccon, <strong>B. Koopman</strong>, and J. Palotti. <i><a href="papers/ecir2015_circumlocation_health_search.pdf">Diagnose this if you can: On the effectiveness of search engines in finding medical self-diagnosis information</a></i>. In European Conference on Information Retrieval (ECIR), April 2015. <span class="short">Short paper</span> <a href="https://github.com/ielab/ecir2015-DignoseThisIfYouCan"> <span class="data">Data</span></a></li>
</ul>
<h3>2014</h3>
<ul class=publications reversed="reversed" start="31">
<li><strong>Bevan Koopman</strong>. <i><a href="papers/sigir_forum2014-SemanticSearchAsInference.pdf">Semantic search as inference: Applications in health informatics</a></i>. SIGIR Forum, 48(2):116-117, December 2014. <span class="journal">Journal</span></li>
<li><strong>B. Koopman</strong> and G. Zuccon. <i><a href="papers/adcs2014-timespan.pdf">Document timespan normalisation and understanding temporality for clinical records search.</a></i> In Proceedings of the 19th Australasian Document Computing Symposium, Melbourne, Australia, November 2014. <span class="short">Short paper</span></li>
<li>S. Mirhosseini, G. Zuccon, <strong>B. Koopman</strong>, A. Nguyen, and M. Lawley. <i><a href="papers/adcs2014-mapping.pdf">Medical free-text to concept mapping as an information retrieval problem: An initial investigation</a></i>. In Proceedings of the 19th Australasian Document Computing Symposium, Melbourne, Australia, November 2014. <span class="short">Short paper</span></li>
<li>G. Zuccon, <strong>B. Koopman</strong>, and P. Bruza. <i><a href="papers/esair2014_inference4IR.pdf">Exploiting inference from semantic annotations for information retrieval: Reflections from medical IR</a></i>. In Seventh International Workshop on Exploiting Semantic Annotations in Information Retrieval, Shanghai, China, November 2014. <span class="workshop">Workshop paper</span></li>
<li>L. Sitbon, M. Kholghi, G. Zuccon, A. Nguyen, <strong>B. Koopman</strong>, and M. Lawley. <i><a href="papers/MQClinicalNLP-Info_Extraction.pdf">Delivering clinical information extraction tools to practitioners</a></i>. In Macquarie University Workshop on Natural Language of Clinical Text (MQClinicalNLP), Sydney, Australia, September 2014. <span class="workshop">Workshop paper</span></li>
<li>G. Zuccon, <strong>B. Koopman</strong>, and P. Bruza. <i><a href="papers/mqclinicalnlp2014_inference4IR.pdf">Towards exploiting inference from semantic annotations for medical information retrieval</a></i>. In Macquarie University Workshop on Natural Language of Clinical Text (MQClinicalNLP), Sydney, Australia, September 2014. <span class="workshop">Workshop paper</span></li>
<li>L. D. Vine, G. Zuccon, <strong>B. Koopman</strong>, L. Sitbon, and P. Bruza. <i><a href="papers/cikm2014_w2vsemsimilarity.pdf">Medical semantic similarity with a neural language model</a>.</i> In 23rd ACM International Conference on Information and Knowledge Management (CIKM), Shanghai, China, November 2014. <span class="short">Short paper</span></li>
<li><strong>B. Koopman</strong> and G. Zuccon. <i><a href="papers/medIR2014-relevance_assessment.pdf">Why assessing relevance in medical IR is demanding</a></i>. In Proceedings of the SIGIR Workshop on Medical Information Retrieval (MedIR), Gold Coast, Australia, July 2014. <span class="workshop">Workshop paper</span> <a href="https://github.com/ielab/MedIR2014-RelanceAssessment"><span class="data">Data</span></a></li>
<li>G. Zuccon and <strong>B. Koopman</strong>. <i><a href="papers/medIR2014_healthsearch_readability.pdf">Integrating understandability in the evaluation of consumer health search engines</a></i>. In Proceedings of the SIGIR Workshop on Medical Information Retrieval (MedIR), Gold Coast, Australia, July 2014. <span class="workshop">Workshop paper</span></li>
<li><strong>B. Koopman</strong> and G. Zuccon. <i><a href="papers/sigir2014_relevation.pdf">Relevation!: An open source system for information retrieval relevance assessment</a></i>. In Proceedings of the 37th annual international ACM SIGIR conference on research and development in information retrieval, Gold Coast, Australia, July 2014. <a href="#" onclick="toggle_visibility('sigir2014-relevation'); return false;">[abstract]</a> <span class="demo">Demo paper</span> <a href="https://github.com/ielab/relevation"> <span class="data">Code</span></a></a></li>
<blockquote id="sigir2014-relevation" class="abstract">
Relevation! is a system for performing relevance judgements for information retrieval evaluation. Relevation! is web-based, fully configurable and expandable; it allows researchers to effectively collect assessments and additional qualitative data. The system is easily deployed allowing assessors to smoothly perform their relevance judging tasks, even remotely. Relevation! is available as an open source project <a href="http://ielab.github.io/relevation">http://ielab.github.io/relevation</a>.
</blockquote>
<li><strong>B. Koopman</strong> and G. Zuccon. <i><a href="papers/sigir2014-negation.pdf">Understanding negation and family history to improve clinical information retrieval</a></i>. In Proceedings of the 37th annual international ACM SIGIR conference on research and development in information retrieval, Gold Coast, Australia, July 2014. <a href="#" onclick="toggle_visibility('sigir2014-negation'); return false;">[abstract]</a> <span class="short">Short paper</span></li>
<blockquote id="sigir2014-negation" class="abstract">
We present a study to understand the effect that negated terms (e.g., ``no fever") and family history (e.g., ``family history of diabetes") have on searching clinical records. Our analysis is aimed at devising the most effective means of handling negation and family history. In doing so, we explicitly represent a clinical record according to its different content types: negated, family history and normal content; the retrieval model weights each of these separately. Empirical evaluation shows that overall the presence of negation harms retrieval effectiveness while family history has little effect. We show negation is best handled by weighting negated content (rather than the common practise of removing or replacing it). However, we also show that many queries benefit from the inclusion of negated content and that negation is optimally handled on a per-query basis. Additional evaluation shows that adaptive handing of negated and family history content can have significant benefits.
</blockquote>
<li><strong>Bevan Koopman</strong>. <i><a href="phd.html">Semantic search as inference: Applications in health informatics</a></i>. PhD Thesis, Queensland University of Technology, May 2014. <span class="book">PhD Thesis</span></li>
</ul>
<h3>2013</h3>
<ul class=publications reversed="reversed" start="20">
<li><strong>B. Koopman</strong>, G. Zuccon, L. De Vine, A. Bakharia, P. Bruza, L. Sitbon, and A. Gibson. <i><a href="papers/adcs2013-adcs_impact.pdf">ADCS reaches adulthood: an analysis of the conference and its community over the last eighteen years</a></i>. In Proceedings of the 18th Australasian Document Computing Symposium, pages 34-41, Brisbane, Australia, December 2013. <span class="long">Long paper</span> <a href="https://github.com/ielab/adcs_adulthood"> <span class="data">Data</span></a></li>
<li>G. Zuccon, <strong>B. Koopman</strong>, and A. Nguyen. <i><a href="papers/clef2013_t3_workingnotes.pdf">Retrieval of health advice on the web: AEHRC at Share/CLEF 2013 eHealth Evaluation Lab Task 3</a></i>. In Proceedings of CLEF Workshop on Cross-Language Evaluation of Methods, Applications, and Resources for eHealth Document Analysis, Valencia, Spain, September 2013. <span class="long">Long paper</span></li>
<li>G. Zuccon, A. Holloway, <strong>B. Koopman</strong>, and A. Nguyen. <i><a href="papers/clef2013_t1_workingnotes.pdf">Identify disorders in health records using conditional random fields and metamap: AEHRC at Share/CLEF 2013 eHealth Evaluation Lab Task 1</a></i>. In Proceedings of CLEF Workshop on Cross-Language Evaluation of Methods, Applications, and Resources for eHealth Document Analysis, Valencia, Spain, September 2013. <span class="long">Long paper</span></li>
<li>M. Symonds, P. Bruza, G. Zuccon, <strong>B. Koopman</strong>, L. Sitbon, and I. Turner. <i><a href="papers/jasist2013-tqe.pdf">Automatic query expansion: a structural linguistic perspective</a></i>. Journal of the American Society for Information Science and Technology (JASIST), In Press, 2013. <span class="journal">Journal</span></li>
<li>Wittek, P., <strong>Koopman, B.</strong>, Zuccon, G. and Daranyi, S., 2013. <i><a href="papers/complex_space.pdf">Combining Word Semantics within Complex Hilbert Space for Information Retrieval</a></i>. In Quantum Interaction. Leicester, UK. <span class="long">Long paper</span></li>
<li>Anthony Nguyen, Derek Ireland, Guido Zuccon, Deanne Vickers, <strong>Bevan Koopman</strong>, Michael Lawley, 2013. <i><a href="papers/BigData2013_queue.pdf">Streaming medical report analytics at increasingly "Big Data" scale</a></i>. In Big Data in Health. Melbourne, Australia. <span class="long">Long paper</span></li>
</ul>
<h3>2012</h3>
<ul class=publications reversed="reversed" start="15">
<li>Symonds, M., Zuccon, G., <strong>Koopman, B.</strong> and Bruza, P., 2012. <i><a href="papers/webtrack2012-word_associations.pdf">QUT Para at TREC 2012 Web Track : Word Associations for Retrieving Web Documents</a></i>. In Proceedings of 21st Text REtrieval Conference (TREC 2012). <span class="long">Long paper</span></li>
<li><strong>Bevan Koopman</strong>, Zuccon, G., Nguyen, A., Vickers, D., Butt, L. and Bruza, P., 2012. <i><a href="papers/med_track-2012.pdf">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</a></i>. In Proceedings of 21st Text REtrieval Conference (TREC 2012). <span class="long">Long paper</span></li>
<li>Zuccon, G., <strong>Koopman, B.</strong>, Nguyen, A., Vickers, D. and Butt, L., 2012. <i><a href="papers/adcs2012_subsumption.pdf">Exploiting Medical Hierarchies for Concept-based Information Retrieval</a></i>. In Proceedings of the Seventeenth Australasian Document Computing Symposium. <span class="short">Short paper</span></li>
<li><strong>Koopman, B.</strong>, Bruza, P., Zuccon, G., Lawley, M. and Sitbon, L., 2012. <i><a href="papers/adcs2012-graph.pdf">Graph-based Concept Weighting for Medical Information Retrieval</a></i> [<a href="papers/ADCS2012GraphIR-Slides.pdf">Slides</a>]. In Proceedings of the Seventeenth Australasian Document Computing Symposium. <a href="#" onclick="toggle_visibility('adcs2012graph'); return false;">[abstract]</a> <span class="long">Long paper</span></li>
<blockquote id="adcs2012graph" class="abstract">
This paper presents a graph-based method to weight med- ical concepts in documents for the purposes of information retrieval. Medical concepts are extracted from free-text doc- uments using a state-of-the-art technique that maps n-grams to concepts from the SNOMED CT medical ontology. In our graph-based concept representation, concepts are vertices in a graph built from a document, edges represent associations between concepts. This representation naturally captures dependencies between concepts, an important requirement for interpreting medical text, and a feature lacking in bag- of-words representations.
We apply existing graph-based term weighting methods to weight medical concepts. Using concepts rather than terms addresses vocabulary mismatch as well as encapsu- lates terms belonging to a single medical entity into a sin- gle concept. In addition, we further extend previous graph- based approaches by injecting domain knowledge that esti- mates the importance of a concept within the global medical domain.
Retrieval experiments on the TREC Medical Records col- lection show our method outperforms both term and concept baselines. More generally, this work provides a means of integrating background knowledge contained in medical ontologies into data-driven information retrieval approaches.
</blockquote>
<li>Symonds, M., Zuccon, G., <strong>Koopman, B.</strong>, Bruza, P. and Nguyen, A.N., 2012. <i><a href="papers/alta2012-medical_judgements.pdf">Semantic Judgement of Medical Concepts: Combining Syntagmatic and Paradigmatic Information</a></i>. In Australasian Language Technology Workshop. <span class="long">Long paper</span></li>
<li><strong>Koopman, B.</strong>, Zuccon, G., Bruza, P., Sitbon, L., & Lawley, M. <i><a href="papers/cikm2012-semantic_similarity.pdf">An Evaluation of Corpus-driven Measures of Medical Concept Similarity for Information Retrieval</a></i>. 21st ACM International Conference on Information and Knowledge Management (CIKM). Maui, USA, October 2012. <span class="short">Short paper</span></li>
<li><strong>Koopman, B.</strong>, Bruza, P., Sitbon, L., Lawley, M. (2012). <i><a href="papers/amj2012-towards_semantic.pdf">Towards Semantic Search and Inference in Electronic Medical Records: an approach using Concept-based Information Retrieval</a></i>. Australasian Medical Journal: Special Issue on Artificial Intelligence in Health, 5(9), pp.482-488. <span class="journal">Journal</span></li>
</ul>
<h3>2011</h3>
<ul class=publications reversed="reversed" start="8">
<li><strong>B. Koopman</strong>, P. Bruza, L. Sitbon, and M. Lawley, <i><a href="papers/med_track-2011.pdf">AEHRC & QUT at TREC 2011 Medical Track : a concept-based information retrieval approach</a></i>. Proceedings of 20th Text REtrieval Conference (TREC 2011), Gaithersburg, MD, USA, November 2011. <span class="long">Long paper</span></li>
<li><strong>Koopman, B.</strong>, Bruza, P., Sitbon, L., Lawley, M. <i><a href="papers/koopman-ai_health-2011.pdf">Towards semantic search and inference in electronic medical records: an approach using concept-based information retrieval</a>.</i> Proceedings of the 1st Australian Workshop on Artificial Intelligence in Health (AIH 2011), Perth, December 2011. <span class="long">Long paper</span></li>
<li><strong>Koopman, B.</strong>, Bruza, P., Sitbon, L., Lawley, M. <i><a href="papers/pp0135-koopman.pdf">Evaluating medical information retrieval</a>.</i> Proceedings of the 34st annual international ACM SIGIR conference on research and development in information retrieval, Beijing, August 2011. <span class="short">Short paper</span></li>
</ul>
<h3>2010</h3>
<ul class=publications reversed="reversed" start="5">
<li><strong>Koopman, B.</strong>, Bruza, P., Sitbon, L., Lawley, M. <i><a href="papers/negation_ir.pdf">Analysis of the effect of negation on information retrieval of medical data</a>.</i> Proceedings of the Fifteenth Australasian Document Computing Symposium (ADCS), Melbourne, December 2010. <span class="short">Short paper</span></li>
<li><strong>Koopman, B.</strong>, Bruza, P., Lawley, M., Sitbon, L. <i><a href="papers/ictc10-semantic.pdf">Semantic search and inferencing in health informatics</a>.</i> Proceedings of the 2010 CSIRO ICT Conference, Sydney, November 2010. <span class="short">Short paper</span></li>
</ul>
<h3>2000-</h3>
<ul class=publications reversed="reversed">
<li>Hunter J., Schroeter R., <strong>Koopman B.</strong>, Henderson M. <a href="http://www.semanticgrid.org/GGF/ggf11/"><i>Using the Semantic Grid to Build Bridges between Museums and Indigenous Communities.</i></a> Global Grid Forum: Semantic Grid Application Workshop, Hawaii. June 2004.<span class="long">Long paper</span></li>
<li>Hunter J., <strong>Koopman B.</strong>, Sledge J. <a href="http://www.archimuse.com/mw2003/papers/hunter/hunter.html"><i>Software Tools for Indigenous Knowledge Management</i></a>. Museums and the Web 2003, September 2003. <span class="long">Long paper</span></li>
<li><strong>Koopman, B.</strong> <a href="http://eprint.uq.edu.au/archive/00000093/"><i>Software Tools for Indigenous Knowledge Management</i></a>. Honours Thesis. School of Information Technology and Electrical Engineering, University of Queensland, Brisbane. 2002. <span class="book">Honours Thesis</span></li>
</ul>
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