In this paper we describe our study on organic topic recognition and knowledge extraction from online documents. Firstly we will introduce the current state of information extraction with ontology support then we will present our approach, corpus, theoretical background, algorithm, experiments and research goals. At the end we will draw some conclusions and show some future research directions.

Lungu, I., Pazienza, M.t., Tudorache, A. (2009). Organic topic recognition in online documents. ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH(4), 73-85.

Organic topic recognition in online documents

PAZIENZA, MARIA TERESA;
2009-10-01

Abstract

In this paper we describe our study on organic topic recognition and knowledge extraction from online documents. Firstly we will introduce the current state of information extraction with ontology support then we will present our approach, corpus, theoretical background, algorithm, experiments and research goals. At the end we will draw some conclusions and show some future research directions.
ott-2009
Pubblicato
Rilevanza internazionale
Articolo
Sì, ma tipo non specificato
Settore ING-INF/05 - SISTEMI DI ELABORAZIONE DELLE INFORMAZIONI
English
Con Impact Factor ISI
knowledge management; knowledge extraction; document classification; support vector machines; Sequential Minimal Optimization; organic agriculture; AGROVOC ontology
www.ecocyb.ase.ro/pdfrev/Ion%20Lungu.pdf
Lungu, I., Pazienza, M.t., Tudorache, A. (2009). Organic topic recognition in online documents. ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH(4), 73-85.
Lungu, I; Pazienza, Mt; Tudorache, A
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/65733
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