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Beyond Labels: Leveraging Deep Learning and LLMs for Content Metadata

Agrawal, Saurabh, Trenkle, John, Kawale, Jaya

arXiv.org Artificial Intelligence

Content metadata plays a very important role in movie recommender systems as it provides valuable information about various aspects of a movie such as genre, cast, plot synopsis, box office summary, etc. Analyzing the metadata can help understand the user preferences to generate personalized recommendations and item cold starting. In this talk, we will focus on one particular type of metadata - \textit{genre} labels. Genre labels associated with a movie or a TV series help categorize a collection of titles into different themes and correspondingly setting up the audience expectation. We present some of the challenges associated with using genre label information and propose a new way of examining the genre information that we call as the \textit{Genre Spectrum}. The Genre Spectrum helps capture the various nuanced genres in a title and our offline and online experiments corroborate the effectiveness of the approach. Furthermore, we also talk about applications of LLMs in augmenting content metadata which could eventually be used to achieve effective organization of recommendations in user's 2-D home-grid.


Senior Product Manager, Machine Learning at Tubi - San Francisco, CA; Remote

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Headquartered in San Francisco, Tubi is an ad-supported video-on-demand (AVOD) service with movies and television shows. With over 40,000 titles from every major Hollywood studio, Tubi gives fans of movies and television shows an easy way to discover new content that is available completely free. Tubi's library has something for every member of our diverse audience, and we're committed to building a workforce that reflects that diversity. We're looking for great people who are creative thinkers, self-motivators, and impact-makers looking to help shape the future of streaming. Our services are currently available in the US, Canada, Australia, New Zealand, Mexico, Costa Rica, Ecuador, El Salvador, Guatemala, and Panama.


How FilmRise Uses Artificial Intelligence to Show You What to Watch Next (Video)

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"Everything we're about is data analytics," Fisher told TheWrap. FilmRise works by using data to understand and anticipate what people want to watch and when. The New York City-based company serves as an independent provider for digital streaming that offers up movies and shows to the top platforms. FilmRise now has more than 40,000 hours of content in its library and is the largest third-party content provider to streaming platforms. Titles like "The Riflemen" and "Midsomer Murders" quickly rose as some of their top hits.