From the course: Building Recommender Systems with Machine Learning and AI

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Bleeding edge alert: Mise-en-scene recommendations

Bleeding edge alert: Mise-en-scene recommendations - Python Tutorial

From the course: Building Recommender Systems with Machine Learning and AI

Bleeding edge alert: Mise-en-scene recommendations

- [Instructor] Time for our first bleeding-edge alert. This is where we highlight some new research that looks interesting or promising but hasn't really made it into the mainstream yet with recommender systems. We want you to have all the latest and greatest information in this course. If you're not familiar with the term, we often refer to the current state-of-the-art as leading-edge, but technology that's still so new that it's unproven in the real world can be risky to work with, and so we call that bleeding-edge. Some recent research in content-based filtering has surrounded the use of mise en scene data. Technically, mise en scene refers to the placement of objects in a scene, but the researchers are using this term a bit more loosely to refer to the properties of the scenes in a movie or movie trailer. The idea is to extract properties from the film itself that can be quantified and analyzed and see if we can come up with better movie recommendations by examining the content of…

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