Understanding content-based recommender systems

One of the most common and successful types of recommendations are content-based. The core idea is that if I expressed a preference for a certain set of items, I will most likely be interested in more items that share the same attributes. For example, the fact that I watched Finding Nemo (2003) can be used as an indication that I will be interested in other movies from the animation and comedy genres.

Alternatively, watching one of the original Star Wars movie can be interpreted as a signal that I like other movies from the franchise, or movies with Harrison Ford, or directed by George Lucas, or science fiction in general. Indeed, Netflix employs such an algorithm, except at a more granular ...

Get Julia Programming Projects now with the O’Reilly learning platform.

O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.