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A Recommender System from Semantic Traces based on Bayes Classifier

Wang, Ning; Abel, Marie-Hélène; Barthès, Jean-Paul; Negre, Elsa (2015), A Recommender System from Semantic Traces based on Bayes Classifier, in Saad, Inès; Rosenthal-Sabroux, Camille; Gargouri, Faiez, Information and knowledge systems:perspectives and challenges, proceedings of the 2nd International Conference on Knowledge Management, Information and Knowledge Systems (KMIKS 2015), Sfax University Press : Sfax, p. 49-60

Type
Communication / Conférence
External document link
https://hal.archives-ouvertes.fr/hal-01266499
Date
2015
Conference title
2nd International Conference on Knowledge Management, Information and Knowledge Systems (KMIKS 2015)
Conference date
2015-04
Conference city
Hammamet
Conference country
Tunisia
Book title
Information and knowledge systems:perspectives and challenges, proceedings of the 2nd International Conference on Knowledge Management, Information and Knowledge Systems (KMIKS 2015)
Book author
Saad, Inès; Rosenthal-Sabroux, Camille; Gargouri, Faiez
Publisher
Sfax University Press
Published in
Sfax
ISBN
9789938129267
Pages
49-60
Metadata
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Author(s)
Wang, Ning
Heuristique et Diagnostic des Systèmes Complexes [Compiègne] [Heudiasyc]
Abel, Marie-Hélène cc
Heuristique et Diagnostic des Systèmes Complexes [Compiègne] [Heudiasyc]
Barthès, Jean-Paul
Heuristique et Diagnostic des Systèmes Complexes [Compiègne] [Heudiasyc]
Negre, Elsa
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Abstract (EN)
Collaboration allows integrating knowledge from every participant to achieve individual or collective goals. Thanks to informational environments, we can better organize, realize and record collaboration. Every activity produces a set of traces. With the help of a model of competency, traces contribute to evaluate the competency of users on a certain subject. In this article, we propose a semantic model of traces and analyze classified traces by means of a Bayes classifier. We exploit the results to offer users recommendations and decision aid.
Subjects / Keywords
Recommender system; Bayes classifier; competency, semantic modelling; trace of interaction