An inference is made regarding whether or not an upcoming day is going to be a busy day for a user. One or more different user-specific event parameters are utilized to compute a user busyness score for the upcoming day, where these parameters are based in part on a history of events for the user and their past behavior. Then, whenever the user busyness score for the upcoming day is greater than a busy day threshold, it is inferred that the upcoming day is going to be a busy day for the user. Whenever the user busyness score for the upcoming day is less than a quiet day threshold, it is inferred that the upcoming day is going to be a quiet day for the user.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A system for inferring whether or not an upcoming day is going to be a busy day for a user, comprising: a busy day inferrer comprising one or more computing devices, said computing devices being in communication with each other via a computer network whenever there is a plurality of computing devices, and a computer program having a plurality of sub-programs executable by said computing devices, wherein the sub-programs configure said computing devices to, utilize one or more different user-specific event parameters to compute a user busyness score for the upcoming day, said parameters being based in part on a history of events for the user and their past behavior, and whenever the user busyness score for the upcoming day is greater than a busy day threshold, infer that the upcoming day is going to be a busy day for the user. 2. The system of claim 1, wherein said parameters comprise one or more of: one or more explicit user-specific event parameters; or one or more inferred user-specific event parameters. 3. The system of claim 2, wherein the explicit user-specific event parameters comprise one or more of: a number of meetings scheduled for the user on a specific day of a specific week; or a cumulative duration of said meetings; or a number of reminders existing for the user on the specific day of the specific week. 4. The system of claim 2, wherein the inferred user-specific event parameters comprise one or more of: a number of pending tasks the user is assigned to complete on a specific day of a specific week; or a number of commutes made by the user on the specific day of the specific week; or a cumulative duration of said commutes. 5. The system of claim 1, wherein the upcoming day coincides with a specific day of a week and the sub-program for utilizing one or more different user-specific event parameters to compute a user busyness score for the upcoming day comprises sub-programs for: for each of said user-specific event parameters, computing a value for the user-specific event parameter on the upcoming day, computing a value for the user-specific event parameter on said specific day of each of a prescribed number of past weeks, computing an historic weighted average of the user-specific event parameter over the prescribed number of past weeks, and using the value for the user-specific event parameter on the upcoming day and the historic weighted average of the user-specific event parameter over the prescribed number of past weeks to compute a user busyness score for the user-specific event parameter, and using a weighted combination of the user busyness scores that are computed for said user-specific event parameters to compute the user busyness score for the upcoming day. 6. The system of claim 5, wherein the prescribed number of past weeks is nine. 7. The system of claim 5, wherein the weight applied to each user-specific event parameter to compute the historic weighted average is initialized to a value defined by a prescribed function that decreases over the prescribed number of past weeks. 8. The system of claim 7, wherein the prescribed function comprises one of: a linear function having a negative slope; or an exponentially decreasing function. 9. The system of claim 5, wherein the weight applied to each user busyness score computed for each user-specific event parameter is initialized to a generic value which is subsequently adjusted over time based upon explicit feedback that is received from the user. 10. The system of claim 9, wherein the generic value is computed as one divided by the total number of said parameters that are utilized. 11. The system of claim 9, wherein the generic value is based upon one of: an analysis of the history of events for the user and their past behavior; or a study that asks one or more users to rank each of the different user-specific event parameters with regard to how good a busyness indicator it is in comparison to the other ones of said parameters. 12. The system of claim 1, wherein the busy day threshold is dynamically determined based on factors comprising the history of events for the user, their past behavior, and past user busyness scores that were computed for the user. 13. The system of claim 1, wherein the sub-program for inferring that the upcoming day is going to be a busy day for the user comprises a sub-program for notifying the user that the upcoming day is going to be a busy day for them. 14. The system of claim 1, wherein the sub-programs further configure said computing devices to, whenever the user busyness score for the upcoming day is less than a quiet day threshold, infer that the upcoming day is going to be a quiet day for the user. 15. The system of claim 14, wherein the quiet day threshold is dynamically determined based on factors comprising the history of events for the user, their past behavior, and past user busyness scores that were computed for the user. 16. The system of claim 14, wherein the sub-program for inferring that the upcoming day is going to be a quiet day for the user comprises a sub-program for notifying the user that the upcoming day is going to be a quiet day for them. 17. A system for inferring whether or not an upcoming day is going to be a busy day for a user, comprising: a busy day inferrer comprising a computing device that is utilized by the user, and a computer program having a plurality of sub-programs executable by said computing device, wherein the sub-programs configure said computing device to, utilize one or more different user-specific event parameters to compute a user busyness score for the upcoming day, said parameters being based in part on a history of events for the user and their past behavior, and whenever the user busyness score for the upcoming day is greater than a busy day threshold, infer that the upcoming day is going to be a busy day for the user. 18. The system of claim 17, wherein said parameters comprise one or more of: a number of meetings scheduled for the user on a specific day of a specific week; or a cumulative duration of said meetings; or a number of reminders existing for the user on the specific day of the specific week; or a number of pending tasks the user is assigned to complete on the specific day of the specific week; or a number of commutes made by the user on the specific day of the specific week; or a cumulative duration of said commutes. 19. The system of claim 17, wherein the upcoming day coincides with a specific day of a week and the sub-program for utilizing one or more different user-specific event parameters to compute a user busyness score for the upcoming day comprises sub-programs for: for each of said user-specific event parameters, computing a value for the user-specific event parameter on the upcoming day, computing a value for the user-specific event parameter on said specific day of each of a prescribed number of past weeks, computing an historic weighted average of the user-specific event parameter over the prescribed number of past weeks, and using the value for the user-specific event parameter on the upcoming day and the historic weighted average of the user-specific event parameter over the prescribed number of past weeks to compute a user busyness score for the user-specific event parameter, and using a weighted combination of the user busyness scores that are computed for said user-specific event parameters to compute the user busyness score for the upcoming day. 20. A computer-implemented process for inferring whether or not an upcoming day is going to be a busy day for a user, the process comprising the actions of: utilizing one or more different user-specific event parameters to compute a user busyness score for the upcoming day, said parameters being based in part on a history of events for the user and their past behavior, and whenever the user busyness score for the upcoming day is greater than a busy day threshold, inferring that the upcoming day is going to be a busy day for the user.