Advances in Knowledge Discovery and Management : Volume 5. [elektronicky zdroj]

Autor: Guillet, Fabrice

Externí odkaz: Kolekce e-knih KNAV (Registrovani uzivatele: plny text online 5 minut, dalsi pristup na vyzadani. Registered users: full text online 5 minutes, further access on requests.)

Advances in Knowledge Discovery and Management, Volume 2. [electronic resource]

Autor: Guillet, Fabrice

Externí odkaz: Kolekce e-knih KNAV Registrovani uzivatele: plny text online 5 minut, dalsi pristup na vyzadani. Registered users: full text online 5 minutes, further access on requests.

Comparing of Term Clustering Frameworks for Modular Ontology Learning

Autor: Xu, Ziwei, Harzallah, Mounira, Guillet, Fabrice

Publikováno v: 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, Sep 2018, Seville, Spain. SCITEPRESS - Science and Technology Publications; SCITEPRESS - Science and Technology Publications, pp.128-135, 2018, Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD

This paper aims to use term clustering to build a modular ontology according to core ontology from domain-specific text. The acquisition of semantic knowledge focuses on noun phrase appearing with the same syntactic roles in relation to a verb or its

Externí odkaz: http://arxiv.org/abs/1901.09037

Qualité, Fouille et Gestion des Connaissances

Autor: Guillet, Fabrice

Qualité, Fouille et Gestion des Connaissances Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Sed non risus. Suspendisse lectus tortor, dignissim sit amet, adipiscing nec, ultricies sed, dolor. Cras elementum ultrices diam. Maecenas ligula

Externí odkaz: http://tel.archives-ouvertes.fr/tel-00481938
http://tel.archives-ouvertes.fr/docs/00/48/19/38/PDF/hdr-F.Guillet.20.10.2006.pdf

Post-Processing of Discovered Association Rules Using Ontologies

Autor: Marinica, Claudia, Guillet, Fabrice, Briand, Henri

Publikováno v: The Second International Workshop on Domain Driven Data Mining (DDDM 2008) in IEEE International Conference of Data Mining, Pisa : Italie (2008)

In Data Mining, the usefulness of association rules is strongly limited by the huge amount of delivered rules. In this paper we propose a new approach to prune and filter discovered rules. Using Domain Ontologies, we strengthen the integration of use

Externí odkaz: http://arxiv.org/abs/0910.0349