Call for Papers Semantics-Enabled Biomedical Information Retrieval

Call for Papers
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Supplement on Semantics-Enabled Biomedical Information Retrieval
Journal of Bio-Medical Semantics

Important Data
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Submission Deadline: December 19th, 2014
Notification of acceptance/rejection: February 27th, 2015
Camera-Ready Paper Deadline: April 17th, 2015
Webpage: http://bioasq.org/project/bioasq-special-issue
Submission page: https://easychair.org/conferences/?conf=jbmsbioir2015

Call
***

Every day, approximately 3000 new bio-medical articles are published on 
the Web. This averages to more than 2 articles every minute. In addition 
to the sheer amount of bio-medical information available on the Web, the 
variety of this information increases everyday and ranges from 
structured data in the form of ontologies to unstructured data in the 
form of documents. Staying on top of this huge amount of diverse data 
requires methods that allow detecting and integrating portions of 
datasets that satisfy the information need of given users from sources 
such as documents, ontologies, Linked Data sets, etc. Developing tools 
to achieve this bold goal requires combining techniques from several 
disciplines including Natural Language Processing (e.g., question 
answering, document summarization, ontology verbalization), Information 
Retrieval (e.g., document and passage retrieval), Machine Learning 
(e.g., large-scale hierarchical classification, clustering, etc.), 
Semantic Web/Linked Data (e.g., reasoning, link discovery) and Databases 
(e.g., storage and retrieval of triples, indexing, etc.).

The aim of this supplement is to collect and present the newest results 
from these domains in order to push the research frontier towards 
information systems that will be able to deal with the whole diversity 
of the Web in the bio-medical domain.

The topics of interest include (but are not restricted to):

* Large-scale hierarchical text classification
* Large-scale classification of documents onto ontology concepts 
(semantic indexing)
* Classification of questions onto ontological concepts
* Scalable approaches to document clustering
* Text summarization, especially multi-document and query-focused 
summarization
* Verbalization of structured information and related queries (RDF, OWL, 
SPARQL, etc.)
* Question Answering over structured, semi-structured and unstructured data
* Reasoning for information retrieval and question answering
* Information retrieval over fragmented sources of information
* Efficient indexing and storage structures for information retrieval
* Delivery of the retrieved information in a concise and 
user-understandable form
* Relation extraction
* Textual entailment
* Natural-language generation
* Named entity recognition/disambiguation
* Fact checking
* Exploitation of semantic resources (terminologies, ontologies) for 
information retrieval and question answering
* Normalisation of data resources with semantic resources, i.e., 
concept-driven data transformation

Cheers,
Axel

-- 
Axel Ngonga, Dr. rer. nat
Head of AKSW
Augustusplatz 10
Room P905
04109 Leipzig
http://aksw.org/AxelNgonga

Tel: +49 (0)341 9732341
Fax: +49 (0)341 9732239

Received on Friday, 19 September 2014 06:04:26 UTC