Method, apparatus, and computer program product for system resource volume prediction

1. A system for predicting one or more transaction terminations associated with a plurality of device rendered objects, the system comprising

a server communicably coupled with a communication network, the server having a processor, the processor, when executing computer-readable instructions, is configured to:

receive first transaction data and second transaction data, the first transaction data comprising a first timestamp and the second transaction data comprising a second timestamp, wherein the first and second transaction data are associated with a device rendered object of the plurality of device rendered objects, the second transaction occurring subsequent to the first transaction;

receive system transaction data, wherein the system transaction data comprises a plurality of attributes associated with a plurality of users, a network time interval and a system wide transaction count occurring during the network time interval;

determine, using a clustering technique, one or more first attributes from the plurality of attributes associated with the system transaction data, the first transaction data, the second transaction data and the device rendered object;

determine, based on the one or more first attributes associated with the first transaction data, the second transaction data, the device rendered object and the system transaction data, a first prediction value that indicates a programmatically expected number of system wide transaction terminations for a future network time interval; and

responsive to determining that system resources are required to fulfill transaction terminations associated with the first prediction value exceeding a system resource allocation threshold, allocate a system resource volume for correcting transaction terminations during the future network time interval.

2. The system of claim 1 , wherein each transaction termination is associated with a required system resource allocation defining an aggregation of network assets that is allocated to be available for fulfillment of network asset requests.

3. The system of claim 1 , wherein the one or more first attributes include one or more of a category for the device rendered object, GPS coordinates associated with the device rendered object, historical data associated with the category of the first device rendered object, and historical data associated with other device rendered objects having the same category as the first device rendered object.

4. The system of claim 1 , wherein the processor is further configured to:

receive third transaction data and fourth transaction data, the third transaction data comprising a third timestamp and the fourth transaction data comprising a fourth timestamp, wherein the third and fourth transaction data are associated with a second device rendered object of the plurality of device rendered objects, the fourth transaction occurring subsequent to the third transaction;

determine, using the clustering technique, one or more second attributes from the plurality of attributes associated with the system transaction data, the third transaction data, the fourth transaction data and the second device rendered object; and

determine, based on the one or more second attributes associated with the third transaction data, the fourth transaction data, the second device rendered object, and the system transaction data, a second prediction value that indicates a programmatically expected number of system wide transaction terminations for a future network time interval, the second prediction value different from the first prediction value.

5. The system of claim 4 , wherein the processor is further configured to: determine, based on values of second attributes different from the first attributes, a third prediction indicating a programmatically expected number of system wide transaction terminations for a future network time interval.

6. The system of claim 1 , wherein determining the first prediction is based on a machine learning model.

7. The system of claim 1 , wherein the second transaction data represents a transaction termination.

8. The system of claim 7 , wherein the fourth transaction data represents a transaction termination.

9. The system of claim 3 , wherein the one or more first attributes corresponds to historical data associated with the GPS coordinates associated with the first device rendered object.

10. The system of claim 9 , wherein the historical data comprises data associated with device rendered objects having GPS coordinates that differ from the GPS coordinates of the first device rendered object by a distance threshold.

11. The system of claim 1 , wherein the processor is further configured to transmit device rendered objects to a network asset requester device based on the first prediction value to influence a reduction in the programmatically expected number of termination transactions.

12. An apparatus for predicting one or more transaction terminations associated with a plurality of device rendered objects, the apparatus comprising at least one processor and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to:

receive first transaction data and second transaction data, the first transaction data comprising a first timestamp and the second transaction data comprising a second timestamp, wherein the first and second transaction data are associated with a device rendered object of the plurality of device rendered objects, the second transaction occurring subsequent to the first transaction;

receive system transaction data, wherein the system transaction data comprises a plurality of attributes associated with a plurality of users, a network time interval and a system transaction count occurring during the network time interval;

determine, using a clustering technique, one or more first attributes from the plurality of attributes associated with the system transaction data, the first transaction data, the second transaction data and the device rendered object;

determine, based on the one or more first attributes associated with the first transaction data, the second transaction data, the device rendered object and the system transaction data, a first prediction value that indicates a programmatically expected number of system wide transaction terminations for a future network time interval; and

responsive to determining that system resources are required to fulfill transaction terminations associated with the first prediction value exceeding a system resource allocation threshold, allocate a system resource volume for correcting transaction terminations during the future network time interval.

13. The apparatus of claim 12 , wherein each transaction termination is associated with a required system resource allocation defining an aggregation of network assets that is allocated to be available for fulfillment of network asset requests.

14. The apparatus of claim 12 , wherein the one or more first attributes include one or more of a category for the device rendered object, GPS coordinates associated with the device rendered object, historical data associated with the category of the first device rendered object, and historical data associated with other device rendered objects having the same category as the first device rendered object.

15. The apparatus of claim 12 , wherein the processor is further configured to:

receive third transaction data and fourth transaction data, the third transaction data comprising a third timestamp and the fourth transaction data comprising a fourth timestamp, wherein the third and fourth transaction data are associated with a second device rendered object of the plurality of device rendered objects, the fourth transaction occurring subsequent to the third transaction;

determine, using the clustering technique, one or more second attributes from the plurality of attributes associated with the system transaction data, the third transaction data, the fourth transaction data and the second device rendered object; and

determine, based on the one or more second attributes associated with the third transaction data, the fourth transaction data, the second device rendered object, and the system transaction data, a second prediction value that indicates a programmatically expected number of system wide transaction terminations for a future network time interval, the second prediction value different from the first prediction value.

16. The apparatus of claim 15 , wherein the processor is further configured to: determine, based on values of second attributes different from the first attributes, a third prediction indicating a programmatically expected number of transaction terminations for a future network time interval.

17. The apparatus of claim 12 , wherein determining the first prediction is based on a machine learning model.

18. The apparatus of claim 12 , wherein the second transaction data represents a transaction termination.

19. The apparatus of claim 12 , wherein the fourth transaction data represents a transaction termination.

20. The apparatus of claim 12 , wherein the historical data comprises data associated with device rendered objects having GPS coordinates that differ from GPS coordinates of the first device rendered object by a distance threshold.

21. The apparatus of claim 12 , wherein the processor is further configured to: transmit device rendered objects to a network asset requester device based on the first prediction value to influence a reduction in the programmatically expected number of termination transactions.