Recommender Systems Essay

705 WordsApr 22, 20133 Pages
Communications 2540 7/11/12 Sites like Amazon.com and Netflix.com now have a customizable feature in which they suggest new and different items that are similar to ones you may have purchased or looked at in the past. They have a recommender system, which is a system that brings up items of the same genre as one you chose in the past. That’s not the only thing these systems can do, the systems now will try to predict what you are going to look for next by either using a matrix of what others bought(amazon) or by analyzing your watching patterns(Netflix). They are similar in a way that they both use a recommender system to further ease your shopping or watching experience. They both give you a wide selection that matched a specific genre of items you may have viewed in the past. They differ however in the aspect of how they try to predict your results. As mentioned above, Amazon uses a matrix of what others bought along with your product and Netflix gives you suggestions based on what you watched before or what your favorite types of movies are. An example for Amazon would be if you bought a wooden chair that was part of a set of wooden furniture that others usually bought with it, it would suggest that you should buy the set with it on the side. Netflix on the other hand, let’s say you watched a comedy film, will suggest a couple comedy films that are related to the film you just watched and will try to match up as many genres as possible. The rating system for Amazon is not very hard to understand but sometimes very hard to trust. The ratings in Amazon can’t always be trusted because some of the items may have ten good reviews and zero bad reviews but the product can still be bad. Sometimes but not that often, the seller can add many of their own “anonymous “ positive reviews to bring others into believing that the product is great, even though it isn’t.

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