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On the other hand, how to effectively mine long tail items has become one of the problems that need to be solved in recommender systems.

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At the end of this review, we discuss negative and positive aspects of these papers, as well as point out opportunities, challenges and possible future research directions.

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In order to remove this, we normalize our data. We show through examples that the embedding of the algorithm in the user experience dramatically affects the value to the user of the recommender.


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