Abstract: This disclosure describes systems and method for implementing a multi-view deep learning framework to map users and items to a latent space and determine similarities between users and preferred items. The multi-view deep learning framework can extract features from a domain space based at least in part on having an adequate interaction history to learn relevant user behavior patterns. The deep learning framework may leverage the learned user behavior patterns across multiple domain spaces to provide useful recommendations related to different domain spaces, including domain spaces of which a user has had little or no previous interaction. Example domain spaces include, but are not limited to, search engines, computing device applications, games, informational services, movie services, music services, and reading services.