Customizable data aggregating, data sorting, and data transformation system
First Claim
1. A system, comprising:
- a memory that stores instructions; and
a processor that executes the instructions to perform operations, the operations comprising;
applying a first filter to a sample of data corresponding to a plurality of measurable actions performed by a plurality of objects to generate a first filtered sample of data corresponding to a first subset of the plurality of measurable actions;
calculating a mean value for each of the plurality of measurable actions in the first filtered sample of data and a standard deviation value for each of the plurality of measurable actions in the first filtered sample of data;
selecting a first set of raw measurements for a first set of measurable actions for a first object of the plurality of objects, wherein the first set of measurable actions correspond to the first subset of the plurality of measureable actions;
calculating a z-score for each of the measurable actions in the first set of measurable actions, wherein the z-score is calculated based on the mean value, the standard deviation value, and the first set of raw measurements;
calculating, based on a weight to be applied to each z-score for each of the measurable actions in the first set of measurable actions, a weighted z-score for each of the measureable actions in the first set of measurable actions;
aggregating each weighted z-score for each of the measurable actions in the first set of measurable actions to generate a first score for the first object; and
comparing the first score for the first object to other scores for other objects in the plurality of objects to determine a ranking for the first object with respect to the other objects.
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Abstract
A customizable data aggregating, data sorting, and data transformation system is disclosed. In particular, the system may allow for the application of various filters to a sample of data corresponding to various measurables associated with objects. A mean and standard deviation for each of the measurables in the filtered sample of data may be calculated and may be utilized in determining z-scores for a first set of raw measurements corresponding to the measurables. Once the z-scores for the first set of raw measurements are determined, selected weights may be applied to each of the z-scores to determine a weighted z-score for each of the measurables in the first set. Each weighted z-score may then be aggregated to generate a score for an object associated with the first set. The score for the object may be utilized to rank the object relative to other objects in the filtered sample of data.
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Citations
20 Claims
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1. A system, comprising:
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a memory that stores instructions; and a processor that executes the instructions to perform operations, the operations comprising; applying a first filter to a sample of data corresponding to a plurality of measurable actions performed by a plurality of objects to generate a first filtered sample of data corresponding to a first subset of the plurality of measurable actions; calculating a mean value for each of the plurality of measurable actions in the first filtered sample of data and a standard deviation value for each of the plurality of measurable actions in the first filtered sample of data; selecting a first set of raw measurements for a first set of measurable actions for a first object of the plurality of objects, wherein the first set of measurable actions correspond to the first subset of the plurality of measureable actions; calculating a z-score for each of the measurable actions in the first set of measurable actions, wherein the z-score is calculated based on the mean value, the standard deviation value, and the first set of raw measurements; calculating, based on a weight to be applied to each z-score for each of the measurable actions in the first set of measurable actions, a weighted z-score for each of the measureable actions in the first set of measurable actions; aggregating each weighted z-score for each of the measurable actions in the first set of measurable actions to generate a first score for the first object; and comparing the first score for the first object to other scores for other objects in the plurality of objects to determine a ranking for the first object with respect to the other objects. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. A method, comprising:
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applying, by utilizing instructions from a memory that are executed by a processor, a first filter to a sample of data corresponding to a plurality of measurable actions performed by a plurality of objects to generate a first filtered sample of data corresponding to a first subset of the plurality of measurable actions; calculating a mean value for each of the plurality of measurable actions in the first filtered sample of data and a standard deviation value for each of the plurality of measurable actions in the first filtered sample of data; selecting a first set of raw measurements for a first set of measurable actions for a first object of the plurality of objects, wherein the first set of measurable actions correspond to the first subset of the plurality of measureable actions; calculating a z-score for each of the measurable actions in the first set of measurable actions, wherein the z-score is calculated based on the mean value, the standard deviation value, and the first set of raw measurements; calculating, based on a weight to be applied to each z-score for each of the measurable actions in the first set of measurable actions, a weighted z-score for each of the measureable actions in the first set of measurable actions; aggregating each weighted z-score for each of the measurable actions in the first set of measurable actions to generate a first score for the first object; and comparing the first score for the first object to other scores for other objects in the plurality of objects to determine a ranking for the first object with respect to the other objects. - View Dependent Claims (15, 16, 17, 18, 19)
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20. A computer-readable device comprising instructions, which when loaded and executed by a processor, cause the processor to perform operations comprising:
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applying a first filter to a sample of data corresponding to a plurality of measurable actions performed by a plurality of objects to generate a first filtered sample of data corresponding to a first subset of the plurality of measurable actions; calculating a mean value for each of the plurality of measurable actions in the first filtered sample of data and a standard deviation value for each of the plurality of measureable actions in the first filtered sample of data; selecting a first set of raw measurements for a first set of measurable actions for a first object of the plurality of objects, wherein the first set of measurable actions correspond to the first subset of the plurality of measureable actions; calculating a z-score for each of the measurable actions in the first set of measurable actions, wherein the z-score is calculated based on the mean value, the standard deviation value, and the first set of raw measurements; calculating, based on a weight to be applied to each z-score for each of the measurable actions in the first set of measurable actions, a weighted z-score for each of the measureable actions in the first set of measurable actions; aggregating each weighted z-score for each of the measurable actions in the first set of measurable actions to generate a first score for the first object; and comparing the first score for the first object to other scores for other objects in the plurality of objects to determine a ranking for the first object with respect to the other objects.
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Specification