Please consider contributing and/or forwarding to appropriate
colleagues and groups.
****We apologize for the multiple copies of this e-mail******
----------------------------------------------------------------------------------------------------------------------------- First Call for Participation ---TRAINING DATA AVAILABLE--- ---------------------------------------------------------------------------------------------------------------------------- *eHealth-KD 2020: eHealth Knowledge Discovery*
*Webpage*: https://knowledge-learning.github.io/ehealthkd-2020/
*Competition environment link:*TO BE ANNOUNCED
*Datasets and tools:*https://github.com/knowledge-learning/ehealthkd-2020/tree/master/data
/Held as part of the evaluation forum IberLEF in the XXXVI edition of the International Conference of the Spanish Society for Natural Language Processing (SEPLN 2020). September 22-25, 2020. Málaga, Spain./
*/Novelties/*/: This edition will involve an additional scenario in which an alternative domain (not health related) will be evaluated, to experience with *transfer learning techniques*./
eHealth-KD 2020 challenge, as part of the IberLEF 2020 Workshop, proposes in its third edition modelling the human language in a scenario in which electronic health documents could be machine readable from a semantic point of view. With this task, it is expected to encourage the development of software technologies to automatically extract a large variety of knowledge from electronic Health documents written in the *Spanish Language*.
This involves two subtasks:
1. Entity recognition
<https://knowledge-learning.github.io/ehealthkd-2020/tasks#subtask-a-entity-recognition>
2. Relation extraction
<https://knowledge-learning.github.io/ehealthkd-2020/tasks#subtask-b-relation-extraction>
The challenge will be managed and played by means of the Codalab
Competitions platform. In addition, the Organization Committee of
eHealth-KD encourages participants to submit a description paper of
their systems. Submitted papers will be reviewed by a scientific
committee, and only accepted papers will be *published at CEUR*. The
proceedings of eHealth-KD will be jointly published with the
proceedings of all the tasks of IberLEF 2020. The submitted *papers*
will be *peer-reviewed* by a Program Committee which is composed by
all the participants in the task eHealth-KD and the Organization
Committee.
We encourage the entire research community and especially those
groups working in *knowledge discovery* and *transfer
learning* technologies to participate in this task. If you are
interested in participating, please browse the following link
https://knowledge-learning.github.io/ehealthkd-2020/.
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HOW TO PARTICIPATE
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1. *Join the Google Group* for the task:
_https://groups.google.com/forum/#!forum/ehealth-kd_
2. *Download the datasets*, examples, scoring scripts and baselines
(if needed) from:
https://github.com/knowledge-learning/ehealthkd-2020/tree/master/data and
fill the following form: https://forms.gle/pUJutSDq2FYLwNWQA
3. *TRAIN your system (ACTIVE)*: Train your models and evaluate your
approach by using the evaluation scripts provided at:
https://github.com/knowledge-learning/ehealthkd-2020
4. *Register at: *TO BE ANNOUNCED
5.* TEST your system*: Submit your results on the test sets at: TO
BE ANNOUNCED
6. *Submit your working notes*. More details in
https://knowledge-learning.github.io/ehealthkd-2020/#Publication%20instructions
7. *Come to Málaga//*/September 22, 2020 /to attend the discussion
of the results of IberLEF evaluation campaigns at a workshop
collocated with SEPLN 2020.
/Lets do it!/
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