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
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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
