Semantics-aware Recommender Systems exploiting Linked Open Data and graph-based features

WWW '18: The Web Conference 2018 Lyon France April, 2018, pp. 457-460, 2018.

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Abstract:

In this contribution we propose a hybrid recommendation framework based on classification algorithms such as Random Forests and Naive Bayes, which are fed with several heterogeneous groups of features. We split our features into two classes: classic features, as popularity-based, collaborative and content-based ones, and extended features...More

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