DocumentCode
2186527
Title
A platform for semantic annotations and ontology population using conditional random fields
Author
Grilheres, Bruno ; Canu, Stephane ; Beauce, Christophe ; Brunessaux, Stephan
Author_Institution
CNRS, CRIHS, Val de Reuil, France
fYear
2005
fDate
19-22 Sept. 2005
Firstpage
790
Lastpage
793
Abstract
Ontologies are widely used for organising and sharing knowledge. But elaborating these resources is a heavy and time-consuming task. This paper is two-fold: it describes EADS DCS text-mining platform, in particular, its service to annotate documents with semantic tags and it presents its extension for incremental learning of ontologies. Domain experts are assisted in the ontology population task by recent machine learning techniques (i.e. conditional random fields). Comparisons are made between annotations from the ontology and from a trained CRF model, so as to detect candidate instances. An iterative process controlled by the experts results in knowledge discovery and constitution of an accurate ontology.
Keywords
data mining; learning (artificial intelligence); ontologies (artificial intelligence); text analysis; EADS DCS; conditional random field; document annotation; incremental learning; knowledge discovery; knowledge organisation; knowledge sharing; machine learning; ontology population; semantic annotation; semantic tags; text-mining; Application software; Constitution; Data mining; Distributed control; Filtering algorithms; Humans; Machine learning; Ontologies; Process control; XML;
fLanguage
English
Publisher
ieee
Conference_Titel
Web Intelligence, 2005. Proceedings. The 2005 IEEE/WIC/ACM International Conference on
Print_ISBN
0-7695-2415-X
Type
conf
DOI
10.1109/WI.2005.10
Filename
1517956
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