Call for Participation: Second BioASQ challenge on large-scale biomedical semantic indexing and question answering

BioASQ challenge on large-scale biomedical semantic indexing and question answering (part of the CLEF 2014 QA track to take place in Sheffield, UK, 15-18 September, 2014)
                   Web site: http://bioasq.org/
                twitter: https://twitter.com/bioasq
             CLEF-QA site: http://nlp.uned.es/clef-qa/
 
The BioASQ challenge consists of two different tasks (Task 2a and Task 2b).
If you are interested in any of the following areas:
* Large-scale and hierarchical classification
* Machine learning
* Semantic Indexing, semantic similarity
then you may want to participate in BioASQ Task 2a (large-scale biomedical semantic indexing).
 
More information at http://bioasq.org/participate/challenges#Task2a
 
If you are interested in any of the following areas:
* Question answering from unstructured and structured data
* Single and multi-document summarization
* Information retrieval and passage retrieval
* Semantic indexing, semantic similarity and reasoning
* Machine learning, classification, learning to rank
* Named-entity recognition and disambiguation
* Information extraction, fact checking, relation extraction
* Textual entailment
* Natural-language generation
 
then you may want to participate in BioASQ Task 2b (biomedical semantic QA).
More information at http://bioasq.org/participate/challenges#Task2b
 
Important dates:
* Task 2a: You can join anytime from February 03, 2014 onwards. New data sets will be released weekly.
* Task 2b: You can join on ANY of the following dates:
  - March 05, 2014
  - March 19, 2014
  - April 02, 2014
  - April 16, 2014
  - April 30, 2014.
 
Detailed schedule at http://bioasq.org/participate/schedule
Training data for both tasks available at http://bioasq.lip6.fr/
Prizes: http://www.bioasq.org/participate/prizes.
 
The BioASQ challenge and workshop are organised by the BioASQ project, supported by the European Commission within the 7th Framework Programme (Grant Agreement No. 318652).