Dynamic classification of time-series categorical data
US-12111851-B1 · Oct 8, 2024 · US
US10025829B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-10025829-B2 |
| Application number | US-201414578226-A |
| Country | US |
| Kind code | B2 |
| Filing date | Dec 19, 2014 |
| Priority date | Dec 19, 2014 |
| Publication date | Jul 17, 2018 |
| Grant date | Jul 17, 2018 |
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A computer-implemented method for analyzing organizational performance from episodic data is provided. Event objects for events is maintained in a database. A trigger for notifying beginning of an event is received. An event object is generated in response to the trigger. Activity data is created for the event object and each of the activity data includes notes of a subjective nature having received and messages of an objective nature. Each of the activity data is associated with event tags. Each of the event objects is classified in an event class and the event class includes a pattern of parameters. Analytics of the event objects is performed based on the event tags and the event class. Filters received from a reviewer is defined for search. A list of the analytics of the event objects which pattern of parameters matches with the filters is displayed on a display.
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What is claimed is: 1. A computer-implemented method for analyzing organizational performance, comprising the steps of: maintaining a plurality of event objects for events in a database, comprising: receiving a trigger for notifying the 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, the activity data comprising structured and unstructured data items describing an event activity that occurred during the event; and associating the activity data with one or more tags; performing analytics of the event objects in the database, comprising: for each event object, identifying the event class, parameters of the event class, and the set of activity data for that event object; and computing a value of each of the parameters using at least one of the tags, the structured data, and the unstructured data of the associated activity data; periodically updating the analytics of the event objects based on newly added activity data; displaying the updated analytics of the event objects at a certain time interval; and utilizing the updated analytics to perform at least one of identifying one or more event objects requested by a user and comparing performances of events of at least two of the event objects by comparing each of the parameter values for one of the event objects with corresponding parameter values for another event object and calculating the performances based on differences in the parameter values of the event object and the other event object, wherein a non-transitory computer readable storage medium stores code for execution on a computer system that performs the method steps. 2. A method according to claim 1 , wherein the event objects requested by the user are identified, comprising: receiving from a reviewer, one or more search filters for the event objects; matching a threshold number of the search filters with at least one of the event class and at least a portion of the parameter values of one or more of the event objects; and displaying the event objects with the matching event class and parameter values on a display. 3. A method according to claim 1 , further comprising: displaying the set of activity data for the event object in real time on a display, comprising at least one of: displaying a log of the activity data comprising a chronological listing of the activity data based on a time when the activity data is created; displaying a map of the activity data based on places where the activity data is created; and displaying a chart of the parameter values for the event object. 4. A method according to claim 1 , further comprising: organizing the event class in a taxonomy; and assigning one or more of event classes to the event object. 5. A method according to claim 1 , further comprising: defining the parameters as at least one of numerical data, transitions, and description of the activity data. 6. A method according to claim 1 , further comprising: analyzing the activity data before incorporating the activity data into the event object, comprising: defining one or more items of the activity data as the structured data items when the activity data items are capable of automatic processing; and defining one or more items of the activity data as the unstructured data items when the activity data items cannot be recognized as processable data. 7. A method according to claim 1 , further comprising at least one of: defining the tags as contexts of the activity data; and defining the tags as purposes of the activity data. 8. A method according to claim 2 , further comprising: identifying one or more of the event objects each associated with one of the event class or at least a portion of the parameter values that do not match the filters for search as outside near misses; and displaying the outside near misses with the displayed list of event objects. 9. A method according to claim 2 , further comprising: identifying one or more of the event objects within the displayed list of event objects that match a minimal number of the search filters for inclusion in the list as inside near misses; and highlighting the inside near misses within the list of event objects. 10. A method according to claim 1 , wherein the event classes comprise at least one of planned events and unplanned events.
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