SYSTEMS AND METHODS FOR DETERMINING AND MANAGING PROBABILITY OF ATTENDANCE

1 . A system, comprising:

a processor comprising instructions maintained in a non-transitory storage that when read by the processor cause the processor to perform:

receiving a request for a prospective meeting comprising a plurality of invitees;

accessing a calendaring data storage comprising data records maintaining records defining a calendar for each of the plurality of invitees each calendar comprising calendar events;

for each of the plurality of invitees, determining a timeframe from a plurality of timeframes for the prospective meeting that has the largest number of the plurality of invitees determined to attend the prospective meeting; and

wherein ones of the invitees are determined to attend the prospective meeting upon determining the corresponding calendar for the ones of the invitees indicates for the timeframe of the prospective meeting, at least one of, availability or a conflict and wherein the conflict is further determined to not be attended.

2 . The system of claim 1 , wherein for ones of the invitees the processor determines whether the conflict will not be attended further comprises, upon determining the conflict is an instance of a recurring event, further determining ones of the invitees did not attended a number of prior instances of the recurring event that greater than a previously defined threshold.

3 . The system of claim 1 , wherein for ones of the invitees the processor determines whether the conflict will not be attended further comprises, upon determining the conflict is an instance of a recurring event, further determining ones of the invitees did not actively participant in a number of prior instances of the recurring event that greater than a previously defined threshold.

4 . The system of claim 1 , wherein for ones of the invitees the processor determines whether the conflict will not be attended further comprises, upon determining the conflict is a meeting having an identified presenter that does not match the ones of the invitees.

5 . The system of claim 1 , wherein for ones of the invitees the processor determines whether the conflict will not be attended further comprises, upon determining the conflict is a meeting having an identified meeting organizer that does not match the ones of the invitees.

6 . The system of claim 1 , further comprising the processor:

accessing an organizational structure record;

determining, for ones of the invitees having the corresponding calendar indicating the conflict with the prospective meeting further comprises the conflict having a very important person in attendance and wherein the very important person is identified as a superior within the organizational structure record; and

wherein the ones of invitees are determined not to attend the conflict upon the conflict being determined to be devoid a very important person.

7 . The system of claim 1 , wherein the processor determines whether ones of the invitees having the corresponding calendar indicating the conflict with the prospective meeting further comprises the processor providing the prospective meeting to a neural network trained to determine a likelihood of attendance and receiving an attendance decision for the conflict therefrom.

8 . The system of claim 7 , wherein the processor further performs:

collecting a set of past event records from a database scheduled for a number of invitees;

applying one or more transformations to each past event including changing attendance, a time of day, changing day of week, changing attendance of a superior, changing the presenter, changing the organizer, to create a modified set of past meeting records;

creating a first training set comprising the collected set of past event records, the modified set of past event records, and a set of non-attended event records;

training the neural network in a first stage using the first training set;

creating a second training set for a second stage of training comprising the first training set and the set of non-attended event records that have attendance incorrectly determined; and

training the neural network in the second stage using the second training set.

9 . The system of claim 8 , wherein the set of non-attended event records comprises the set of past event records that comprise indicia of attendance for at least one invitee that was absent therefrom.

10 . The system of claim 1 , wherein the processor automatically moves indicia of each of a plurality of candidate timeslots for the prospective meeting closets to a starting location based on the number of the plurality invitees determined to attend.

11 . A method, comprising:

receiving a request for a prospective meeting comprising a plurality of invitees;

accessing a calendaring data storage comprising data records maintaining records defining a calendar for each of the plurality of invitees each calendar comprising calendar events;

for each of the plurality of invitees, determining a timeframe from a plurality of timeframes for the prospective meeting that has the largest number of the plurality of invitees determined to attend the prospective meeting; and

wherein ones of the invitees are determined to attend the prospective meeting upon determining the corresponding calendar for the ones of the invitees indicates for the timeframe of the prospective meeting, at least one of, availability or a conflict and wherein the conflict is further determined to not be attended.

12 . The method of claim 11 , wherein determining whether, for ones of the invitees, the conflict will not be attended further comprises, upon determining the conflict is an instance of a recurring event, determining ones of the invitees did not attended a number of prior instances of the recurring event that greater than a previously defined threshold.

13 . The method of claim 11 , determining whether, for ones of the invitees, the conflict will not be attended further comprises, upon determining the conflict is an instance of a recurring event, determining ones of the invitees did not actively participant in a number of prior instances of the recurring event that greater than a previously defined threshold.

14 . The method of claim 11 , wherein determining whether, for ones of the invitees, the conflict will not be attended further comprises determining whether the conflict is a meeting having an identified presenter that does not match the ones of the invitees.

15 . The method of claim 11 , wherein determining whether, for ones of the invitees, the conflict will not be attended further comprises determining whether the conflict is a meeting having an identified meeting organizer that does not match the ones of the invitees.

16 . The method of claim 11 , further comprising:

accessing an organizational structure record;

determining, for ones of the invitees having the corresponding calendar indicating the conflict with the prospective meeting further comprises the conflict having a very important person in attendance and wherein the very important person is identified as a superior within the organizational structure record; and

wherein the ones of invitees are determined not to attend the conflict upon the conflict being determined to be devoid a very important person.

17 . The method of claim 11 , wherein determining whether, for ones of the invitees, the corresponding calendar indicating the conflict with the prospective meeting further comprises providing the prospective meeting to a neural network trained to determine a likelihood of attendance and receiving an attendance decision for the conflict therefrom.

18 . The method of claim 17 , further comprising:

collecting a set of past event records from a database scheduled for a number of invitees;

applying one or more transformations to each past event including changing attendance, a time of day, changing day of week, changing attendance of a superior, changing the presenter, changing the organizer, to create a modified set of past meeting records;

creating a first training set comprising the collected set of past event records, the modified set of past event records, and a set of non-attended event records;

training the neural network in a first stage using the first training set;

creating a second training set for a second stage of training comprising the first training set and the set of non-attended event records that have attendance incorrectly determined; and

training the neural network in the second stage using the second training set.

19 . The method of claim 11 , further comprising

receiving, via a graphical user interface, a user selection to organize each icon based on a specific criteria, wherein the specific criteria is the number of the plurality of invitees determine to attend a prospective meeting occurring at a particular timeslot; and

automatically moving the most used icons to a position on the graphical user interface closest to a previously determined prominent location on the graphical user interface based on the number of the plurality of invitees determine to attend.

20 . A system, comprising:

means to receive a request for a prospective meeting comprising a plurality of invitees;

means to access a calendaring data storage comprising data records maintaining records defining a calendar for each of the plurality of invitees each calendar comprising calendar events;

means to, for each of the plurality of invitees, determine a timeframe from a plurality of timeframes for the prospective meeting that has the largest number of the plurality of invitees determined to attend the prospective meeting; and

wherein ones of the invitees are determined to attend the prospective meeting upon determining the corresponding calendar for the ones of the invitees indicates for the timeframe of the prospective meeting, at least one of, availability or a conflict and wherein the conflict is further determined to not be attended.