- From: Alexander Garcia Castro <alexgarciac@gmail.com>
- Date: Fri, 19 Sep 2014 09:34:18 +0200
- To: Axel Ngonga <ngonga@informatik.uni-leipzig.de>
- Cc: public-lod community <public-lod@w3.org>, "semantic-web@w3.org" <semantic-web@w3.org>, editor1@kdnuggets.com
- Message-ID: <CALAe=OLQG1+cGnL19m4szhYsbgwxGNBzw9zsRd-k0_BDuAQXag@mail.gmail.com>
Hi, I don't mean to be picky. I am just curious about statements like "2 articles every minute". Where do they come from? Where can I get this stats? are this stats about journal papers? if this is true, I assume it is, then shouldn't we start to consider that the quality of publications is simply poor? Perhaps this is a challenge for us to clear the act instead of a challenge for the technology; and if there is a challenge for the tech then, IMHO, it should be how to remove rubbish from those 3000 articles per day "Every day, approximately 3000 new bio-medical articles are published on the Web". Anyway, just woke up this morning and saw this "per day, 3000 new bio-medical articles are published on the Web" and then "2 articles every minute". Just in the biomedical domain and I thought, where does it come from and what does it mean for us. On Fri, Sep 19, 2014 at 8:03 AM, Axel Ngonga < ngonga@informatik.uni-leipzig.de> wrote: > Call for Papers > ************ > Supplement on Semantics-Enabled Biomedical Information Retrieval > Journal of Bio-Medical Semantics > > Important Data > ************* > 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 > > > -- Alexander Garcia http://www.alexandergarcia.name/ http://www.usefilm.com/photographer/75943.html http://www.linkedin.com/in/alexgarciac
Received on Friday, 19 September 2014 07:35:07 UTC