Abstract
In this paper we provide an overview of the fourth edition of the CLEF eHealth evaluation lab. CLEF eHealth 2016 continues our evaluation resource building efforts around the easing and support of patients, their next-of-kins and clinical staff in understanding, accessing and authoring eHealth information in a multilingual setting. This year’s lab offered three tasks: Task 1 on handover information extraction related to Australian nursing shift changes, Task 2 on information extraction in French corpora, and Task 3 on multilingual patient-centred information retrieval considering query variations. In total 20 teams took part in these tasks (3 in Task 1, 7 in Task 2 and 10 in Task 3). Herein, we describe the resources created for these tasks, evaluation methodology adopted and provide a brief summary of participants to this year’s challenges and some results obtained. As in previous years, the organizers have made data and tools associated with the lab tasks available for future research and development.
In alphabetical order, LK & LG co-chaired the lab. HS led Task 1. AN led Task 2. JP & GZ led Task 3.
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Notes
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See our live demostration at http://nicta-stct.s3-website-ap-southeast-2.amazonaws.com, last accessed on 25 May 2016.
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The organisers are thankful to Carnegie Mellon University, and in particular to Jamie Callan and Christina Melucci, for their support in obtaining the permission to redistribute ClueWeb 12. The organisers are also thankful to Microsoft Azure who provided the Azure cloud computing infrastructure that was made available to participants through the Microsoft Azure for Research Award CRM:0518649.
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See http://www.cnts.ua.ac.be/conll2000/chunking/, last accessed on 25 May 2016.
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using https://www.random.org/, last accessed on 25 May 2016.
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The persistence parameter p in RBP was set to 0.8.
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Acknowledgements
The CLEF eHealth 2016 evaluation lab has been supported in part by (in alphabetical order) the ANR, the French National Research Agency, under grant CABeRneT ANR-13-JS02-0009-01; CLEF Initiative; ESF ELIAS network program Horizon 2020 program (H2020-ICT-2014-1) under grant agreement 644753 (KCONNECT); Microsoft Azure for Research Award CRM:0518649; NICTA, funded by the Australian Government through the Department of Communications and the Australian Research Council through the Information and Communications Technology (ICT) Centre of Excellence Program; and PhysioNetWorks Workspaces.
We express our gratitude to Maricel Angel, Registered Nurse at NICTA, for hel** us to create the Task 1 dataset, using the Protégé resource, which is supported by grant GM10331601 from the National Institute of General Medical Sciences of the United States National Institutes of Health. We are also thankful to the people involved in the query creation and relevance assessment exercise. Last but not least, we gratefully acknowledge the participating teams’ hard work. We thank them for their submissions and interest in the lab.
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Kelly, L., Goeuriot, L., Suominen, H., Névéol, A., Palotti, J., Zuccon, G. (2016). Overview of the CLEF eHealth Evaluation Lab 2016. In: Fuhr, N., et al. Experimental IR Meets Multilinguality, Multimodality, and Interaction. CLEF 2016. Lecture Notes in Computer Science(), vol 9822. Springer, Cham. https://doi.org/10.1007/978-3-319-44564-9_24
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