<p>(A–C) Mean personalization. (D–F) Mean novelty. Results are obtained by 10-fold cross-validation experiments on MovieLens (5,000 users and 5,977 objects) with cosine similarity measure. Restart probabilities for random walk approaches are set to 0.9. The higher the mean personalization, the better the recommendation diversity performance. The higher the mean novelty, the better the diversity performance.</p
Abstract. Collaborative filtering and, more generally, recommender systems represent an increasingly...
Recommendation systems have wide-spread applications in both academia and industry. Traditionally, p...
Sales diversity is considered a key feature of Recommender Systems from a business perspective. Sale...
<p>(A–C) Mean relative rank. (D–F) Precision at <i>L</i> = 20. Results are obtained by 10-fold cross...
<p>(A–C) Recall enhancement. (D–F) Hit-rate at <i>L</i> = 20. Results are obtained by 10-fold cross-...
<div><p>Personalized recommender systems have been receiving more and more attention in addressing t...
<p>(A) Mean relative rank. (B) Precision at <i>L</i> = 20. (C) Recall enhancement. (D) Hit-rate at <...
Personalized recommender systems have been receiving more and more attention in addressing the serio...
<p>Results are mean (standard derivation) obtained by 10-fold cross-validation experiments on MovieL...
Recommender system evaluation usually focuses on the overall effectiveness of the algorithms, either...
For recommender systems that base their product rankings primarily on a measure of similarity betwee...
While there has been a lot of research towards improving the accuracy of recommender systems, the re...
Recommender systems has become increasingly important in online community for providing personalized...
Network-based similarity measures have found wide applications in recommendation algorithms and made...
International audienceThe diversity of the item list suggested by recommender systems has been prove...
Abstract. Collaborative filtering and, more generally, recommender systems represent an increasingly...
Recommendation systems have wide-spread applications in both academia and industry. Traditionally, p...
Sales diversity is considered a key feature of Recommender Systems from a business perspective. Sale...
<p>(A–C) Mean relative rank. (D–F) Precision at <i>L</i> = 20. Results are obtained by 10-fold cross...
<p>(A–C) Recall enhancement. (D–F) Hit-rate at <i>L</i> = 20. Results are obtained by 10-fold cross-...
<div><p>Personalized recommender systems have been receiving more and more attention in addressing t...
<p>(A) Mean relative rank. (B) Precision at <i>L</i> = 20. (C) Recall enhancement. (D) Hit-rate at <...
Personalized recommender systems have been receiving more and more attention in addressing the serio...
<p>Results are mean (standard derivation) obtained by 10-fold cross-validation experiments on MovieL...
Recommender system evaluation usually focuses on the overall effectiveness of the algorithms, either...
For recommender systems that base their product rankings primarily on a measure of similarity betwee...
While there has been a lot of research towards improving the accuracy of recommender systems, the re...
Recommender systems has become increasingly important in online community for providing personalized...
Network-based similarity measures have found wide applications in recommendation algorithms and made...
International audienceThe diversity of the item list suggested by recommender systems has been prove...
Abstract. Collaborative filtering and, more generally, recommender systems represent an increasingly...
Recommendation systems have wide-spread applications in both academia and industry. Traditionally, p...
Sales diversity is considered a key feature of Recommender Systems from a business perspective. Sale...