Insertion of Ontological Knowledge to Improve Automatic Summarization Extraction Methods

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ISSN Print: 2150-8402
ISSN Online: 2150-8410
www.scirp.org/journal/jilsa
E-mail: jilsa@scirp.org

"Insertion of Ontological Knowledge to Improve Automatic Summarization Extraction Methods"
written by Jésus Antonio Motta, Laurence Capus, Nicole Tourigny,
published by Journal of Intelligent Learning Systems and Applications, Vol.3 No.3, 2011

has been cited by the following article(s):

[1]	Semantification of Text Through Summarisation
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[2]	CRF Machine Learning Model Reinforced by Ontological Knowledge for Document Summarization
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[3]	Similarity versus relatedness: A novel approach in extractive Persian document summarisation
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[4]	Pembandingan Aplikasi Peringkasan Multi Dokumen menggunakan Sentence Scoring dan Maximum Marginal Relevance dengan K-Means
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[5]	Automatic news summarization method based Maximal Marginal Relevance
	International Core Journal of Engineering, 2016

[6]	VENCE: A New Machine Learning Method Enhanced by Ontological Knowledge to Extract Summaries
	2016

[7]	VENCE: un modèle performant d'extraction de résumés basé sur une approche d'apprentissage automatique renforcée par de la connaissance ontologique
	2014

[8]	VENCE: un modèle performant d'extraction de résumés basé sur une approche d'apprentissage automatique renforcée par de la connaissance …
	2014

[9]	Evaluation of Efficiency of Linear Techniques to Optimize Attribute Space in Machine Learning: Relevant Results for Extractive Methods of Summarizing
	Computer and Information Science, 2012

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[1]	VENCE: A new machine learning method enhanced by ontological knowledge to extract summaries 2016 SAI Computing Conference (SAI), 2016 DOI:10.1109/SAI.2016.7555963