Abstract: A candidate virtual team is generated using a team prediction model. The team prediction model is trained based on user feedback. Activity data of a user is collected, the activity data is associated with activities in which the user and a set of other users have engaged. A candidate virtual team associated with the collected activity data is generated using a team prediction model and the candidate virtual team is presented to the user using an interface. User feedback data associated with the generated candidate virtual team is received from the user. The team prediction model is trained using the received user feedback data, whereby accuracy of future generated candidate virtual teams generated by the team prediction model is improved during the training. The training of the team prediction model based on user feedback improves the generation of virtual teams over time.

Abstract: The disclosure herein describes a system for measuring probability of influence in digital communications to determine if communication content originated in a person's own prior knowledge or new information more recently obtained from interaction with communications of others. An estimated probability a new communication by a first user comes from the same distribution as prior communications of the first user are generated using multidimensional statistics on embeddings representing the communications. A second estimated probability that the new communication comes from the same distribution as communication(s) of a second user that were accessible to the first user are generated. If the second probability is greater than the first probability, the new communication is more likely influenced by exposure of the first user to the second user's communications rather than the first user's own historical knowledge.

Abstract: Systems and methods for inferring and contextualizing a stranger on an enterprise platform are provided. The method includes generating a familiarity score between a user and an individual. Based on the generated familiarity score, the individual is determined to be a stranger to the user and a contextualized summary of the stranger is generated. The generated contextualized summary of the stranger is presented to the user in response to an upcoming interaction between the user and the stranger or a detected interaction between the user and the stranger.