Trust your neighbors: A comprehensive survey of neighborhood-based
methods for recommender systems
- URL: http://arxiv.org/abs/2109.04584v1
- Date: Thu, 9 Sep 2021 23:16:39 GMT
- Title: Trust your neighbors: A comprehensive survey of neighborhood-based
methods for recommender systems
- Authors: Athanasios N. Nikolakopoulos, Xia Ning, Christian Desrosiers, George
Karypis
- Abstract summary: 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.
- Score: 16.874144306491477
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- 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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