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Slope One is a family of algorithms used for collaborative filtering , introduced in a 2005 paper by Daniel Lemire and Anna Maclachlan. [ 1 ] Arguably, it is the simplest form of non-trivial item-based collaborative filtering based on ratings. Their simplicity makes it especially easy to implement them efficiently while their accuracy is often on par with more complicated and computationally expensive algorithms. [ 1 ] [ 2 ] They have also been used as building blocks to improve other algorithms. [ 3 ] [ 4 ] [ 5 ] [ 6 ] [ 7 ] [ 8 ] [ edit ] Item-based collaborative filtering of rated resources and overfitting
Introduction The purpose of this post is to explain how to use Apache Mahout to deploy a massively scalable, high throughput recommender system for a certain class of usecases. I’ll describe the shape of usecases covered and give a step-by-step guide to setting up such a recommender system.
i 41 Votes A recommender engine helps a user find novel and interesting items within a pool of resources.