Abstract
Recommender systems based on unsupervised machine learning algorithms are very popular because they overcome many challenges that collaborative, hybrid, and classification-based systems face. A clustering technique is used to recommend the products/items based on the patterns and behaviors captured within each segment/cluster. This technique is good when data is limited, and there is no labeled data to work with.
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Kulkarni, A., Shivananda, A., Kulkarni, A., Krishnan, V.A. (2023). Clustering-Based Recommender Systems. In: Applied Recommender Systems with Python. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-8954-9_7
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DOI: https://doi.org/10.1007/978-1-4842-8954-9_7
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Publisher Name: Apress, Berkeley, CA
Print ISBN: 978-1-4842-8953-2
Online ISBN: 978-1-4842-8954-9
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