A Survey of Naive Bayesian Algorithms for Similarity in Recommendation Systems

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Provided by: International Journal of Advanced Research in Computer Science and Software Engineering (IJARCSSE)
Topic: Big Data
Format: PDF
The recommendation systems are widely used to support the users to handle the ever increasing data over the internet efficiently. Recommendation systems apply machine learning and data mining techniques for filtering unseen information and can predict whether a user would like a given resource. To date a number of recommendation system algorithms have been proposed such as collaborative filtering recommendations, content based recommendations and hybrid approach algorithms. The focus is generally on content based recommendation systems methods which are mainly based on naive Bayesian machine learning algorithm.
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