Recommendation Engines

Movies & Digital Entertainment

Modern recommendation engines use matching algorithms processing the data and attach tags to the words bearing emotional attitude as well as matching previously mentioned or searched items. On this basis, accurate, relevant and appealing recommendations and suggestions are made.

The providers are eager to develop a content bearing the emotional attachment to a viewer. Thus, the appropriate content would reach the right viewers at the correct time.

Benefits for the company

Recommendation engines give the entertainment and media providers a chance to focus on the users’ desires and feelings



Type of expertise/ AI domain

Deep Learning, Matrix factorization

Internal data required

Consumer Content consumption, interaction data

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