Mécanisme de prédiction pour une plateforme de filtrage collaboratif
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Date
2012
Authors
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Publisher
CERIST, Alger
Abstract
Face à la quantité et la rapidité d’apparition de nouvelles informations le développement de
systèmes d’information pour cibler au mieux les réponses fournies aux utilisateurs afin qu’elles soient
plus proches de leurs attentes et de leurs goûts personnels est devenu une nécessité incontournable.
Les systèmes de filtrage collaboratif s’inscrivent parmi ces systèmes d’information avec certaines
particularités qui font la différence. Le terme de filtrage collaboratif désigne les techniques utilisant les
goûts connus d’un groupe d’utilisateurs pour prédire la préférence inconnue d’un nouvel utilisateur.
Cet article décrit une plateforme de base de filtrage collaboratif qui permet aux utilisateurs la
découverte de documents intéressants, grâce à l’automatisation du processus naturel de
recommandation, elle leur permet d’exprimer leurs avis quant à la pertinence des documents, selon
leurs goûts et la qualité qu’ils perçoivent des documents ; elle offre la possibilité de bénéficier des
évaluations sur les documents que d’autres utilisateurs, de profil proche, ont jugés intéressants. Tous
ces avantages sont apportés aux utilisateurs par le principe de collaboration, en contrepartie d’un
effort individuel : l’évaluation des documents.
With the explosive growth of the quantity of new information the development of information systems to target the best answers provided to users, so they are closer to their expectations and personal taste, has become an unavoidable necessity. The collaborative filtering systems are among these information systems with particular characteristics that make the difference. The term refers to collaborative filtering techniques using the familiar tastes of a group of users to predict the unknown preference of a new user. This article describes a basic platform of collaborative filtering, which allows users to discover interesting documents, through automation of the natural process of recommendation, it allows them to express their opinion about the relevance of documents, according to their tastes and documents’ quality they perceive; it offers the opportunity to benefit from the evaluations on documents of other users, with similar profile, have found interesting. All these benefits are provided to users by the principle of collaboration, in return for an individual effort: evaluating documents.
With the explosive growth of the quantity of new information the development of information systems to target the best answers provided to users, so they are closer to their expectations and personal taste, has become an unavoidable necessity. The collaborative filtering systems are among these information systems with particular characteristics that make the difference. The term refers to collaborative filtering techniques using the familiar tastes of a group of users to predict the unknown preference of a new user. This article describes a basic platform of collaborative filtering, which allows users to discover interesting documents, through automation of the natural process of recommendation, it allows them to express their opinion about the relevance of documents, according to their tastes and documents’ quality they perceive; it offers the opportunity to benefit from the evaluations on documents of other users, with similar profile, have found interesting. All these benefits are provided to users by the principle of collaboration, in return for an individual effort: evaluating documents.
Description
Keywords
Filtrage collaboratif, Communautés, Prédictions, Recommandations, Collaborative filtering, Community, Platform, Predictions, Recommender systems, Plateforme