
AI Blueprints
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Previously, we saw that there are two kinds of recommendations, content-based (Content-based recommendation systems, Pazzani, Michael J., and Daniel Billsus, The Adaptive Web, pp. 325-341, Springer, Berlin, Heidelberg, 2007, https://link.springer.com/chapter/10.1007%2F978-3-540-72079-9_10) and collaborative filtering (Item-based collaborative filtering recommendation algorithms, Sarwar, Badrul, George Karypis, Joseph Konstan, and John Riedl, in Proceedings of the 10th international conference on World Wide Web, pp. 285-295, ACM, 2001, https://dl.acm.org/citation.cfm?id=372071). A content-based recommendation finds similar items to a given item by examining the item's properties, such as its title or description, category, or dependencies on other items (for example, electronic toys require batteries). These kinds of recommendations do not use any information about ratings, purchases, or any other user information (explicit or implicit).
Let's suppose...