Abstract
HTTP cookies are used to monitor web-traffic and track users surfing the Internet. We often notice that promotions (ads) on websites tend to match our needs, reveal our prior browsing history, or reflect our interests. That is not an accident. Nowadays, recommendation systems are highly based on machine learning methods that can learn the behavior, e.g., purchasing patterns, of individual consumers. In this chapter, we will uncover some of the mystery behind recommendation systems based on transactional records. Specifically, we will (1) discuss association rules and their support and confidence; (2) the Apriori algorithm for association rule learning; and (3) cover step-by-step a set of case-studies, including a toy example, Head and Neck Cancer Medications, and Grocery purchases.
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References
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© 2018 Ivo D. Dinov
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Dinov, I.D. (2018). Apriori Association Rules Learning. In: Data Science and Predictive Analytics. Springer, Cham. https://doi.org/10.1007/978-3-319-72347-1_12
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DOI: https://doi.org/10.1007/978-3-319-72347-1_12
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