[cfp] Workshop on Semantic Indexing and Information Retrieval for Health from heterogeneous content types and languages

Deadline Extension: February 3rd, 2020 for open session papers.
https://sites.google.com/view/siirh2020/

Apologies for cross-postings and please help to disseminate

Call for papers
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The First Workshop on Semantic Indexing and Information Retrieval for
Health from heterogeneous content types and languages (SIIRH2020)
Held in conjunction with the 42nd European Conference on Information
Retrieval (ECIR2020)

Workshop
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This workshop will be a forum where the community can present and discuss
current and future directions for the area based on the experience and
results obtained in the BioASQ MESINESP task (http://temu.bsc.es/mesinesp/)..

In addition to the MESINESP session, the workshop will include an Open
Session covering IR technologies for heterogeneous health-related content
open to multiple languages with a particular interest in the exploitation
of structured controlled vocabularies and entity linking.

Open Session Topics
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- multilingual and non-English health related IR, concept indexing and text
categorization strategies;
- generation of evaluation resources for health and biomedical document IR
strategies;
- scalability, robustness and reproducibility of health and biomedical IR
and text mining resources;
- use of specialized machine translation and advanced deep learning
approaches for improving health related search results;
- medical Question Answering search tools;
- retrieval of multilingual health related web-content;
- other related topics.

Important Dates (Open Session)
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Submission Deadline:  **3 February 2020 (11:59pm GMT)**
Acceptance Notification: 28 February 2020 (11:59pm GMT)
Camera Ready Contributions: 30 March 2020 (11:59pm GMT)
Workshop: 14 April 2020 in Lisbon, Portugal

Additional Information
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https://sites.google.com/view/siirh2020/




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Martin Krallinger, Dr.
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Head of Biological Text Mining Unit
Barcelona Supercomputing Center (BSC-CNS)
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Oficina Técnica de sanidad del Plan TL
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