Recommender systems, a class of interactive systems that involve predicting users’ response to options, are key to providing guidance in navigating and accessing vast collections of content or product selection.
Recommender systems leverage on several different technologies to provide suggestions to users, and are mostly used to:
- propose content based on the properties thereof, as in “content based systems”, for example, users that have watched sci-fi movies will be proposed other sci-fi movies which might be of interest
- recommend items based on similarity measurements of users and/or items, as in “collaborative filtering”, where suggestions are created leveraging on the analysis of preferences and/or behavior of similar users
The technologies licensed under this program are used in products and services ranging from digital content distribution services (services for the distribution of digital multimedia content over broadcast and/or broadband network) to e-commerce and social networking platforms. The use of these technologies occurs both in consumer products and in the professional domain.