A basic platform of collaborative filtring
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Date
2008
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CERIST
Abstract
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.
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Keywords
Collaborative filtering, Community, Platform, Predictions, Recommender systems