1. A system that predicts and outputs events identified as being surprising to a person, comprising a memory having stored therein computer executable components and a processor that executes the following computer executable components: an interface component that receives contextual and historical data; a predictive model component that utilizes the contextual and historical data to predict an event and outputs the prediction if the prediction corresponds to one or more definitions of surprise, wherein the prediction corresponds to one or more definitions of surprise based on a probability of occurrence of the event, and wherein the predictive model component comprises: a robust predictive model that generates a prediction of the event based on interdependencies between variables associated with the contextual and historical data, wherein the interdependencies are not contemplated by the person; and a user expectancy model that utilizes the contextual and historical data to generate a prediction of the event based on, at least in part, machine learning and a case library that includes a plurality of surprising events and observations associated with the plurality of surprising events; a difference analyzer component that calculates a measure of difference between the prediction made by the robust predictive model and the prediction made by the user expectancy model to determine whether an event is surprising; and an alerting component that alerts the person of the surprising event upon the determination that the event is surprising.
1. A system that predicts and outputs events identified as being surprising to a person, comprising a memory having stored therein computer executable components and a processor that executes the following computer executable components: an interface component that receives contextual and historical data; a predictive model component that utilizes the contextual and historical data to predict an event and outputs the prediction if the prediction corresponds to one or more definitions of surprise, wherein the prediction corresponds to one or more definitions of surprise based on a probability of occurrence of the event, and wherein the predictive model component comprises: a robust predictive model that generates a prediction of the event based on interdependencies between variables associated with the contextual and historical data, wherein the interdependencies are not contemplated by the person; and a user expectancy model that utilizes the contextual and historical data to generate a prediction of the event based on, at least in part, machine learning and a case library that includes a plurality of surprising events and observations associated with the plurality of surprising events; a difference analyzer component that calculates a measure of difference between the prediction made by the robust predictive model and the prediction made by the user expectancy model to determine whether an event is surprising; and an alerting component that alerts the person of the surprising event upon the determination that the event is surprising. 6. The system of claim 1 , wherein the alerting component utilizes alerting rules to determine a manner in which to alert the person of the surprising event, wherein the alerting rules consider at least one of a type of device carried by the person or time of day.