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arXiv · 2109.04584

Trust your neighbors: A comprehensive survey of neighborhood-based methods for recommender systems

Athanasios N. Nikolakopoulos·Xia Ning·Christian Desrosiers·George Karypis
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Abstract

Collaborative recommendation approaches based on nearest-neighbors are still highly popular today due to their simplicity, their efficiency, and their ability to produce accurate and personalized recommendations. This chapter offers a comprehensive survey of neighborhood-based methods for the item recommendation problem. It presents the main characteristics and benefits of such methods, describes key design choices for implementing a neighborhood-based recommender system, and gives practical information on how to make these choices. A broad range of methods is covered in the chapter, including traditional algorithms like k-nearest neighbors as well as advanced approaches based on matrix factorization, sparse coding and random walks.

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Athanasios N. Nikolakopoulos, Xia Ning, Christian Desrosiers, George Karypis. 2021-09-09. Trust your neighbors: A comprehensive survey of neighborhood-based methods for recommender systems. https://arxiv.org/abs/2109.04584

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