Abstract: Methods, systems and computer program products for recommending remediation actions to selected users of collaboration systems. Certain disclosed techniques commence upon observing user-to-object interactions and user-to-user interactions raised by users of a collaboration system. A first specialized data structure is populated with activity values that characterize user-to-object interactions raised by individual users. A second specialized data structure is populated with sharing values that characterize observed sharing events over shared content objects. The values of the first data structure are correlated to the values of the second data structure to calculate a total contribution amount for each of the users of the collaboration system. A small set of communication recipients is identified by ranking the individual users based on a calculated total contribution amount. To avoid wasteful messaging to all users of the collaboration system, messages are sent only to the small set of recipients.

Abstract: Systems and methods provide techniques for improving application utilization using prediction-based recommendations. In various embodiments, a method includes receiving user engagement data associated with a user-accessed application and an entity identifier of a particular entity and receiving historical user engagement data for additional entities associated with the user-accessed application and at least one of a plurality of candidate applications. The method includes determining a subset of the additional entities using a similarity analysis between the user engagement data and the historical user engagement data. The method includes generating, using a machine learning model, respective recommendation scores for the candidate applications based on the user engagement data, the machine learning model having been trained using a subset of the historical user engagement data corresponding to the subset of additional entities.

Abstract: Methods, systems and computer program products for recommending remediation actions to selected users of collaboration systems. Certain disclosed techniques commence upon observing user-to-object interactions and user-to-user interactions raised by users of a collaboration system. A first specialized data structure is populated with activity values that characterize user-to-object interactions raised by individual users. A second specialized data structure is populated with sharing values that characterize observed sharing events over shared content objects. The values of the first data structure are correlated to the values of the second data structure to calculate a total contribution amount for each of the users of the collaboration system. A small set of communication recipients is identified by ranking the individual users based on a calculated total contribution amount. To avoid wasteful messaging to all users of the collaboration system, messages are sent only to the small set of recipients.