International audienceThis paper provides a service-oriented such solution which explore the ontology based modeling of users and documents in order to provide users with personalized recommendations of resources. Alongside with the adoption of semantic Web technologies for ontology based modeling, our approach aims a better pertinence for recommendations by adopting a hybrid recommendation technique, combining a collaborative filtering and a content-based approach. The collaborative filtering module adopts a Markov decision process in order to predict the next concept which will be focused by the user, tracking the user navigation through ontology instead through the structure of a particular site. The content based recommender module adop...
In recent years, e-learning recommender systems has attracted great attention as a solution towards ...
Recommender systems have emerged in the e-commerce domain and have been developed to actively recomm...
International audienceIn this paper we provide a solution for recommending multimedia materials insi...
International audienceThis paper provides a service-oriented such solution which explore the ontolog...
Personalization and recommendation systems are a solution to the problem of content overload, especi...
International audienceThe current paper expose a solution of personalized recommendations for e-lear...
International audienceInside the e-learning platforms, it is important to be managed the user compet...
The task of the recommendation systems is to recommend items that are relevant to the preferences of...
International audienceThe use of personalized recommender systems to assist users in the selection o...
A recommender system captures the user preferences and behaviour to provide a relevant recommendatio...
Abstract—Personalized recommendation is an effective method to resolve the current problem of Intern...
This paper presents a semantic approach to Recommender Systems (RS), to exploit available contextual...
We describe a recommender system which uses a unique combination of content-based and collaborative ...
We describe a recommender system which uses a unique combination of content-based and collaborative...
With the advance of information technology, people could retrieve and manage their information more ...
In recent years, e-learning recommender systems has attracted great attention as a solution towards ...
Recommender systems have emerged in the e-commerce domain and have been developed to actively recomm...
International audienceIn this paper we provide a solution for recommending multimedia materials insi...
International audienceThis paper provides a service-oriented such solution which explore the ontolog...
Personalization and recommendation systems are a solution to the problem of content overload, especi...
International audienceThe current paper expose a solution of personalized recommendations for e-lear...
International audienceInside the e-learning platforms, it is important to be managed the user compet...
The task of the recommendation systems is to recommend items that are relevant to the preferences of...
International audienceThe use of personalized recommender systems to assist users in the selection o...
A recommender system captures the user preferences and behaviour to provide a relevant recommendatio...
Abstract—Personalized recommendation is an effective method to resolve the current problem of Intern...
This paper presents a semantic approach to Recommender Systems (RS), to exploit available contextual...
We describe a recommender system which uses a unique combination of content-based and collaborative ...
We describe a recommender system which uses a unique combination of content-based and collaborative...
With the advance of information technology, people could retrieve and manage their information more ...
In recent years, e-learning recommender systems has attracted great attention as a solution towards ...
Recommender systems have emerged in the e-commerce domain and have been developed to actively recomm...
International audienceIn this paper we provide a solution for recommending multimedia materials insi...