Comparative Study of Recommendation Algorithms and Systems using WEKA

Abstract

Recommendation systems now days are the heart of success stories for business and optimization of resources. The accurate prediction of business decision accurately depends on heuristic algorithms used for analytics. Classical algorithms used for the data mining find their utility to perform with the new challenges considering key factors for improvement. This paper presents the performance of the specific algorithms of the data mining class in view to observe their suitability for recommender systems.