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Communication Dans Un Congrès Année : 2018

An Improved Collaborative Filtering Recommendation Algorithm for Big Data

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With the increase of volume, velocity, and variety of big data, the traditional collaborative filtering recommendation algorithm, which recommends the items based on the ratings from those like-minded users, becomes more and more inefficient. In this paper, two varieties of algorithms for collaborative filtering recommendation system are proposed. The first one uses the improved k-means clustering technique while the second one uses the improved k-means clustering technique coupled with Principal Component Analysis as a dimensionality reduction method to enhance the recommendation accuracy for big data. The experimental results show that the proposed algorithms have better recommendation performance than the traditional collaborative filtering recommendation algorithm.
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hal-01913907 , version 1 (07-11-2018)

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Hafed Zarzour, Faiz Maazouzi, Mohamed Soltani, Chaouki Chemam. An Improved Collaborative Filtering Recommendation Algorithm for Big Data. 6th IFIP International Conference on Computational Intelligence and Its Applications (CIIA), May 2018, Oran, Algeria. pp.660-668, ⟨10.1007/978-3-319-89743-1_56⟩. ⟨hal-01913907⟩
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