IP Library Patent Application 15688796
Patent Application
App. No. 15/688,796

AUTOMATED APPLICATION ANALYTICS

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Quick Facts
Patent No.
US None
App. No.
15/688,796
Abstract

An application analytics generation system employs data stored in a social networking system's social graph to automatically predict outcomes based on various observed attributes, and transmit these predictions to a social networking system's user interface, e.g., in a newsfeed, for an advertiser or application developer. These predictions correlate various attributes and/or actions to outcomes, e.g., in relation to advertisements or applications.

Claims (47)

1 . A method performed by a computing device having one or more processors and memories, comprising:

receiving a collection of data, wherein the received collection of data includes at least a portion of a social graph, the social graph comprising a data structure representing entities, relationships between the entities, attributes associated with the entities, and events corresponding to actions performed on or by the entities;

receiving, via an application program interface, a request for correlation data, the correlation data correlating the attributes and the actions with outcomes, wherein the outcomes are selected other attributes or actions;

dividing a set of attributes and events not selected as outcomes into a set of dimensions;

grouping the dimensions into two or more groups of dimensions;

correlating the groups of dimensions with the outcomes;

selecting at least one statistically significant correlation between one of the groups of dimensions and the outcomes; and

causing to be displayed in a user interface the selected at least one correlation.

2 . The method of claim 1 , wherein the selecting includes performing a t-test between the two or more groups of dimensions to select the at least one statistically significant correlation.

3 . The method of claim 1 , further comprising receiving from the user interface an indication of whether the displayed at least one correlation is useful.

4 . The method of claim 3 , further comprising using a machine learning algorithm to improve subsequent selections of selected correlations.

5 . The method of claim 1 , wherein the displaying is in a newsfeed of a social network.

6 . The method of claim 5 , further comprising:

selecting multiple correlations;

prioritizing the selected multiple correlations; and

displaying the selected multiple correlations in order of priority.

7 . The method of claim 1 , further comprising receiving via the user interface a selection of a portion of the user interface, the selected portion defining a set of entities having common attributes and, in response, displaying via the user interface a set of additional entities also having the common attributes.

8 . The method of claim 1 , further comprising sorting the groups of dimensions.

9 . The method of claim 1 , wherein the attribute can be age, gender, country, operating system type, operating system version, screen size, memory capacity, or type of data communications network employed.

10 . The method of claim 1 , wherein an attribute can be one or more actions performed on or by an entity.

11 . The method of claim 1 , wherein outcome can be selecting an advertisement, purchasing a product, installing an application, uninstalling an application, or engaging with a feature of an application.

12 . A computer-readable storage device storing instructions, the instructions comprising:

instructions for receiving a collection of data, wherein the received collection of data includes at least a portion of a social graph, the social graph comprising a data structure representing entities, relationships between the entities, attributes associated with the entities, and events corresponding to actions performed on or by the entities;

instructions for receiving, via an application program interface, a request for correlation data, the correlation data correlating the attributes and the actions with outcomes, wherein the outcomes are selected other attributes or actions;

instructions for dividing a set of attributes and events not selected as outcomes into a set of dimensions;

instructions for grouping the dimensions into two or more groups of dimensions;

instructions for correlating the groups of dimensions with the outcomes;

instructions for selecting at least one statistically significant correlation between one of the groups of dimensions and the outcomes; and

instructions for causing to be displayed in a user interface the selected at least one correlation.

13 . The computer-readable storage device of claim 12 , wherein the instructions for selecting include instructions for performing a t-test between the two or more groups of dimensions to select the at least one statistically significant correlation.

14 . The computer-readable storage device of claim 12 , further comprising instructions for receiving from the user interface an indication of whether the displayed at least one correlation is useful.

15 . The computer-readable storage device of claim 14 , further comprising instructions for using a machine learning algorithm to improve subsequent selections of selected correlations.

16 . The computer-readable storage device of claim 16 , further comprising:

instructions for selecting multiple correlations;

instructions for prioritizing the selected multiple correlations; and

instructions for displaying the selected multiple correlations in order of priority.

17 . The computer-readable storage device of claim 12 , further comprising instructions for receiving via the user interface a selection of a portion of the user interface, the selected portion defining a set of entities having common attributes and, in response, displaying via the user interface a set of additional entities also having the common attributes.

18 . The computer-readable storage device of claim 12 , wherein the attribute can be age, gender, country, operating system type, operating system version, screen size, memory capacity, or type of data communications network employed.

19 . The computer-readable storage device of claim 12 , wherein outcome can be selecting an advertisement, purchasing a product, installing an application, uninstalling an application, or engaging with a feature of an application.

20 . A system having one or more processors and memories, comprising:

a component configured to receive a collection of data, wherein the received collection of data includes at least a portion of a social graph, the social graph comprising a data structure representing entities, relationships between the entities, attributes associated with the entities, and events corresponding to actions performed on or by the entities;

a component configured to receive, via an application program interface, a request for correlation data, the correlation data correlating the attributes and the actions with outcomes, wherein the outcomes are selected other attributes or actions;

a component configured to divide a set of attributes and events not selected as outcomes into a set of dimensions;

a component configured to group the dimensions into two or more groups of dimensions;

a component configured to correlate the groups of dimensions with the outcomes;

a component configured to select at least one statistically significant correlation between one of the groups of dimensions and the outcomes; and

a component configured to cause to be displayed in a user interface the selected at least one correlation.

Assignments (2)
CHANGE OF NAME Recorded Dec 28, 2021
From: FACEBOOK, INC.
To: META PLATFORMS, INC.
Reel/Frame 058594/0253 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 25, 2018
From: JONES, LISA; NATARAJAN, RAMKUMAR; TWIST, JONJO
To: FACEBOOK, INC.
Reel/Frame 045902/0857 →