Data processing system with machine learning engine to provide output generation functions
Methods, computer-readable media, systems, and/or apparatuses for providing offer and insight generation functions are provided. For instance, user input may be received requesting generation of an offer. In response to receiving the request, an application may be transmitted to a device, such as a mobile device of a user. In some examples, the application may be executed by the device and may facilitate establishing a communication session with a third party system, identifying and extracting data from the third party system, and transmitting the extracted data to an entity for evaluation. In some examples, evaluation by the entity may include generating one or more insights, outputs and the like. In some arrangements, the evaluation may be performed using machine learning and, in some examples, may be performed in real-time or near real-time.
1 . A computing platform, comprising:
a processing unit comprising a processor; and
a memory unit storing computer-executable instructions, which when executed by the processing unit, cause the computing platform to:
establish a communication session with a computing device of a user;
receive, from the computing device and during the communication session, a request to generate an offer;
receive, from the computing device in response to receiving the request, data extracted by a third party system, the data obtained by the third party system from a plurality of devices of the user, the plurality of devices including the computing device and at least one other device of a different device type, and the data including a first type of data and a second type of data;
filter the first type of data and the second type of data according to at least one privacy protocol to generate filtered data, wherein the at least one privacy protocol filters the first type of data and the second type of data using a time series relationship to favor data from the computing device and remove at least some data from the at least one other device of a different device type;
categorize the filtered data by applying a clustering algorithm to the filtered data wherein applying the clustering algorithm comprises:
analyzing, using a first type of machine learning algorithm, the first type of data to evaluate the user, and
analyzing using a second type of machine learning algorithm different from the first type of machine learning algorithm, the second type of data to evaluate the user;
generate an output based on the categorized data; and
cause the computing device to display the output.
2 . The computing platform of claim 1 , wherein the first type of data is location data corresponding to locations of the computing device at a plurality of days and times.
3 . The computing platform of claim 2 , wherein the first type of data is captured by a global positioning system of the computing device and stored by the third party system.
4 . The computing platform of claim 3 , wherein the first type of data is captured and stored prior to receiving the request to generate the offer.
5 . The computing platform of claim 2 , wherein the first type of data includes a plurality of location entries corresponding to each location of the computing device at a particular day and time.
6 . The computing platform of claim 5 , wherein each location entry includes longitude and latitude coordinates and a time and date stamp.
7 . The computing platform of claim 1 , further including instructions that, when executed, cause the computing platform to generate one or more insights related to the user including at least one of: frequently visited locations, time spent driving within predefined distance of a home location, and distances travelled.
8 . A computing device, comprising:
a processing unit comprising a processor; and
a memory unit storing computer-executable instructions, which when executed by the processing unit, cause the computing device to:
establish a communication session with a computing platform;
transmit, during the communication session and to the computing platform, a request to generate an offer;
receive, from a third party computing system, user data associated with a user, the user data being obtained by the third party computing system from a plurality of devices of the user, the plurality of devices including the computing device and at least one other device of a different device type, and the user data including a first type of data and a second type of data;
transmit the user data received from the third party computing system to the computing platform; and
receive, from the computing platform, a generated output based on the user data, wherein the generated output is generated by filtering the first type of data and the second type of data according to at least one privacy protocol and categorizing the first type of data and the second type of data by applying a clustering algorithm, wherein applying the clustering algorithm comprises analyzing, using a first type of machine learning algorithm, the first type of data to evaluate the user, and analyzing using a second type of machine learning algorithm, the second type of data to evaluate the user,
wherein the at least one privacy protocol filters the first type of data and the second type of data using a time series relationship to favor data from the computing device and remove at least some data from the at least one other device of a different device type.
9 . The computing device of claim 8 , wherein the first type of data is location data corresponding to locations of the computing device at a plurality of days and times.
10 . The computing device of claim 9 , wherein the first type of data is captured by a global positioning system of the computing device and stored by the third party computing system.
11 . The computing device of claim 10 , wherein the first type of data is captured and stored prior to generating the request to generate the offer.
12 . The computing device of claim 10 , wherein the first type of data includes a plurality of location entries corresponding to each location of the computing device at a particular day and time.
13 . The computing device of claim 12 , wherein each location entry includes longitude and latitude coordinates and a time and date stamp.
14 . One or more non-transitory computer-readable media storing computer-executable instructions that, when executed by a computing device, cause the computing device to:
establish a communication session with a computing platform;
transmit, during a communication session and to the computing platform, a request to generate an offer;
receive, from a third party computing system, user data associated with a user, the user data being collected by the third party computing system from a plurality of devices of the user, the plurality of devices including the computing device and at least one other device of a different device type, and the user data including a first type of data and a second type of data;
transmit the user data received from the third party computing system to the computing platform; and
receive, from the computing platform, a generated output based on the user data, wherein the generated output is generated by filtering the user data according to at least one privacy protocol and categorizing, using a clustering algorithm, the first type of data and the second type of data, wherein applying the clustering algorithm comprises analyzing, using a first type of machine learning algorithm, the first type of data to evaluate the user, and analyzing using a second type of machine learning algorithm different from the first type of machine learning algorithm, the second type of data to evaluate the user, and wherein the at least one privacy protocol filters the first type of data and the second type of data using a time series relationship to favor data from the computing device and removes at least some data from the at least one other device of a different device type.
15 . The one or more non-transitory computer-readable media of claim 14 , wherein the first type of data is location data corresponding to locations of the computing device at a plurality of days and times.
16 . The one or more non-transitory computer-readable media of claim 15 , wherein the first type of data is captured by a global positioning system of the computing device and stored by the third party computing system.
17 . The one or more non-transitory computer-readable media of claim 16 , wherein the first type of data is captured and stored prior to generating the request to generate the offer.
18 . The one or more non-transitory computer-readable media of claim 16 , wherein the first type of data includes a plurality of location entries corresponding to each location of the computing device at a particular day and time.
19 . The one or more non-transitory computer-readable media of claim 18 , wherein each location entry includes longitude and latitude coordinates and a time and date stamp.