Abstract: A determination is made that an explanatory data set for a common set of predictions generated by a machine learning model for records containing text tokens is to be provided. Respective groups of related tokens are identified from the text attributes of the records, and record-level prediction influence scores are generated for the token groups. An aggregate prediction influence score is generated for at least some of the token groups from the record-level scores, and an explanatory data set based on the aggregate scores is presented.

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.