l-Injection Toward Effective Collaborative Filtering

CHOPPARI KARUNA, Dr VIJAY REDDY MADIREDDY

Abstract


We develop a novel framework, named as l-injection, to address the sparsity problem of recommender systems. By carefully injecting low values to a selected set of unrated user-item pairs in a user-item matrix, we demonstrate that top-N recommendation accuracies of various collaborative filtering (CF) techniques can be significantly and consistently improved.

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