Abstract
In brick and mortar stores, on the one hand, we have salespeople guiding and recommending to us relevant products while shopping. On the other hand, with online retail platforms, there are zillions of different products available, and we have to navigate ourselves to find the right product. The situation is that users have too many options and choices available, yet they don’t like to invest a lot of time going through the entire catalogue of items. Hence, the role of Recommender Systems (RS) becomes critical for recommending relevant items and driving customer conversion.
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© 2019 Pramod Singh
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Singh, P. (2019). Recommender Systems. In: Machine Learning with PySpark . Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-4131-8_7
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DOI: https://doi.org/10.1007/978-1-4842-4131-8_7
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Publisher Name: Apress, Berkeley, CA
Print ISBN: 978-1-4842-4130-1
Online ISBN: 978-1-4842-4131-8
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