A recommender system using GA K-means clustering in an online shopping market

By Kyoung-jae Kim, Hyunchul Ahn. Expert systems with applications, 2008

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A literature review and classification of recommender systems research (2012, neutral): “…(2007) Association rule Zhang and Jiao (2007) Association rule Pu and Chen (2007) Clustering, link analysis Wang, Dai, and Yuan (2008b) Clustering Kim and Ahn (2008) Association rule, k-NN Wang and Wu (2009) k-NN Albadvi and Shahbazi (2009) Heuristic model Pu and Chen (2009) k-NN Kim et al.…”
Recommender systems survey (2013, methodology): “A common technique to improve the features of RS consists of initially carrying out a clustering on all of the users, in such a way that a group of classes of similar users is obtained, after this, the desired CF techniques can be applied to each of the clusters, obtaining similar results but in muc”
Recommender system application developments: A survey (2015, background): “Genetic algorithms (GA) are stochastic search techniques which are suitable for parameter optimization problems with an objective function subject to hard and soft constraints [42].”
Meta-Learning to Cluster (2019, background): “, 1996] have shown promising results in various applications, such as object recognition [Stockman, 1987] and recommendation systems [Kim and Ahn, 2008].”