In this work we consider the problem of extracting concepts and relations between them from documents, aiming at constructing an index for a more semantically oriented search engine. While assessment is performed on a biomedical application, the proposed solutions can be also applied to different domains. With the distributed architecture proposed, we obtain an approach that can be applied also on large data sets. Experimental assessment has been performed on a standard data set, BioNLP 2013.

A distributed information extraction system integrating ontological knowledge and probabilistic classifiers

Silvestri Stefano
2014

Abstract

In this work we consider the problem of extracting concepts and relations between them from documents, aiming at constructing an index for a more semantically oriented search engine. While assessment is performed on a biomedical application, the proposed solutions can be also applied to different domains. With the distributed architecture proposed, we obtain an approach that can be applied also on large data sets. Experimental assessment has been performed on a standard data set, BioNLP 2013.
2014
Istituto di Calcolo e Reti ad Alte Prestazioni - ICAR - Sede Secondaria Napoli
Inglese
2014 Ninth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing
2014 9th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing, 3PGCIC 2014
420
425
6
9781479941711
http://www.scopus.com/record/display.url?eid=2-s2.0-84946691715&origin=inward
IEEE
New York
STATI UNITI D'AMERICA
Sì, ma tipo non specificato
8-10/11/2014
Guangzhou, Guangdong; China
Information Extraction
Markov Random Fields
Distributed Approach
4
reserved
Alicante, Anita; Benerecetti, Massimo; Corazza, Anna; Silvestri, Stefano
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/339293
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