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May 27, 2019 · An alternate methods of forming peer groups is to use modified k-means clustering to find the nearest users/items for each user/item.
In order to increase the speed of collaborative filtering recommendation in social networks, an improved nearest-neighbor algorithm is proposed in this paper.
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This paper presents a metric to measure similarity between users, which is applicable in collaborative filtering processes carried out in recommender systems.
This short paper reports on work in progress related to applying data partitioning/clustering algorithms to ratings data in collaborative filtering.
Nov 6, 2022 · In collaborative filtering recommender systems, products are regarded as features and users are requested to provide ratings to the products ...
Oct 22, 2024 · This paper proposes an improved collaborative filtering personalized recommendation (ICF) algorithm, which can effectively improve the data ...
In this paper, single-objective hybrid evolutionary approach is proposed for clustering items in the offline collaborative filtering RS.
Dec 22, 2022 · The research combines the improved artificial bee colony algorithm with K-means algorithm and applies them to the recommendation system to form a collaborative ...
Collaborative filtering is the most widely used approach in terms of recommendations for providing services to users. The essence of this approach is to improve ...
We propose a data clustering method that is based on genetic algorithms. We show, based on findings, that this method is faster and more accurate than classic ...