Computer-Implemented System And Method For Performing Event Trend Analysis

1 . A computer-implemented method for performing trend analysis, comprising:

maintaining a plurality of event objects for events in a database, comprising:

receiving a trigger for notifying a beginning of an event;

generating an event object representing the event in response to the trigger;

assigning an event class to the event object, the event class being associated with a predefined set of parameters;

creating a set of activity data for the event object, each activity data comprising structured and unstructured data describing an event activity occurred during the event; and

associating each of the activity data with one or more tags;

for each of the event objects, performing analytics of the event object and calculating values for the parameters of the event object;

defining one time period for trend analysis and previous time periods;

retrieving the set of event objects that occurred during the trend analysis time period;

determining trends among the event objects during the trend analysis time period and among the event objects for the previous time periods;

comparing the trends of the event objects of the trend analysis period with the trends of the event objects for the previous time periods;

identifying significant trend changes between the compared trends;

creating a trend object for each significant trend change; and

analyzing the trend object.

2 . A method according to claim 1 , further comprising:

applying at least one of spatial filters and temporal filters to the retrieved event objects;

matching at least one of the spatial filters and temporal filters with at least one of the event class and the parameter values of the retrieved event objects; and

displaying a list of the retrieved event objects that match at least one of the spatial filters and temporal filters.

3 . A method according to claim 1 , further comprising:

computing for each event object the value of each of the parameters using at least one of the tags, the structured data, and the unstructured data of the activity data.

4 . A method according to claim 1 , further comprising:

receiving a request for trends identified during a specified period of time;

matching the event objects with the requested trends;

retrieving candidates of the event objects that match the requested trends;

identifying a significant change in performance among two or more of the candidate event objects over the specified period of time; and

displaying at least one of the candidate event objects which shows the identified significant change in data as the trend.

5 . A method according to claim 1 , further comprising:

performing fast Fourier analysis to identify rhythms between the event objects.

6 . A method according to claim 1 , further comprising:

reducing a number of the event objects associated with the trend analysis time period by applying one or more filters to the event objects during the trend analysis time period; and

determining trends amongst the event objects that satisfy the filters.

7 . A method according to claim 6 , further comprising at least one of:

when a number of the event objects that satisfy the filters is below a threshold value, ignoring the determined trend for those event objects; and

when a number of the event objects that satisfy the filters is above a threshold value, compare the determined trend for those event objects with the event objects associated with the previous time periods.

8 . A method according to claim 7 , further comprising:

identifying one or more of the trend changes between the event objects that satisfy the threshold value and the event objects associated with the previous time periods; and

determining a size of the trend change.

9 . A method according to claim 8 , further comprising:

ignoring the trend change between the event objects that satisfy the threshold value and the event objects associated with the previous time periods when the determined size of the trend change is small.

10 . A method according to claim 8 , further comprising:

creating the trend object for the trend change between the event objects that satisfy the threshold value and the event objects associated with the previous time periods when the determined size of the trend change is significantly large.

11 . A computer-implemented system for performing trend analysis, comprising:

a database to store a plurality of event objects for events; and

a server comprising a central processing unit, memory, an input port to receive the event objects from the database, and an output port, wherein the central processing unit is configured to:

receive a trigger for notifying a beginning of an event;

generate an event object representing the event in response to the trigger;

assign an event class to the event object, the event class being associated with a predefined set of parameters;

create a set of activity data for the event object, each activity data comprising structured and unstructured data describing an event activity occurred during the event;

associate each of the activity data with one or more tags;

for each of the event objects, perform analytics of the event object and calculate values for the parameters of the event object;

define one time period for trend analysis and previous time periods;

retrieve the set of event objects that occurred during the trend analysis time period;

determine trends among the event obj ects during the trend analysis time period and among the event objects for the previous time periods;

compare the trends of the event objects of the trend analysis period with the trends of the event objects for the previous time periods;

identify significant trend changes between the compared trends;

create a trend object for each significant trend change; and

analyze the trend object.

12 . A system according to claim 11 , wherein the central processing unit performs the following:

apply at least one of spatial filters and temporal filters to the retrieved event objects;

match at least one of the spatial filters and temporal filters with at least one of the event class and the parameter values of the retrieved event objects; and

display a list of the retrieved event objects that match at least one of the spatial filters and temporal filters.

13 . A system according to claim 11 , wherein the central processing unit computes for each event object the value of each of the parameters using at least one of the tags, the structured data, and the unstructured data of the activity data.

14 . A system according to claim 11 , wherein the central processing unit further performs the following:

receive a request for trends identified during a specified period of time;

match the event objects with the requested trends;

retrieve candidates of the event objects that match the requested trends;

identify a significant change in performance among two or more of the candidate event objects over the specified period of time; and

display at least one of the candidate event objects which shows the identified significant change in data as the trend.

15 . A system according to claim 11 , wherein the central processing unit performs fast Fourier analysis to identify rhythms between the event objects.

16 . A system according to claim 11 , wherein the central processing unit reduces a number of the event objects associated with the trend analysis time period by applying one or more filters to the event objects during the trend analysis time period and determines trends amongst the event objects that satisfy the filters.

17 . A system according to claim 16 , wherein the central processing unit performs at least one of:

when a number of the event objects that satisfy the filters is below a threshold value, ignore the determined trend for those event objects; and

when a number of the event objects that satisfy the filters is above a threshold value, compare the determined trend for those event objects with the event objects associated with the previous time periods.

18 . A system according to claim 17 , wherein the central processing unit identifies one or more of the trend changes between the event objects that satisfy the threshold value and the event objects associated with the previous time periods and determines a size of the trend change.

19 . A system according to claim 18 , wherein the central processing unit ignores the trend change between the event objects that satisfy the threshold value and the event objects associated with the previous time periods when the determined size of the trend change is small.

20 . A system according to claim 18 , wherein the central processing unit creates the trend object for the trend change between the event objects that satisfy the threshold value and the event objects associated with the previous time periods when the determined size of the trend change is significantly large.