Recommendation engine accounting for preference drift

A method comprising

• at a computing platform comprising at least one processor, a communication interface, and memory:
• training, using historical preference information, a collaborative recommendation engine, wherein training the collaborative recommendation engine configures the collaborative recommendation engine to output recommendation information based on:
• historical user preference information of various user groups, and
• data drift of the historical preference information for each of the various user groups;
• receiving an account access request from a user device;
• identifying, at a first time and using the collaborative recommendation engine, a preference group for the user device, wherein identifying the preference group is based on a similarity of preferences between the preference group and a user of the user device, and wherein the preference group corresponds to a first set of preferences at the first time;
• providing, to the user device and based on the first set of preferences, first recommendation information;
• receiving, at a second time later than the first time, a second account access request from the user device;
• identifying, using the collaborative recommendation engine, the preference group and data drift corresponding to the preference group between the first time and the second time, wherein the data drift indicates that the preference group corresponds to a second set of preferences at the second time, and wherein identifying the data drift comprises:
• identifying a different preference group that previously corresponded to the first set of preferences;
• identifying that the different preference group transitioned from the first set of preferences to the second set of preferences;
• and
• automatically predicting, based on the transition of the different preference group from the first set of preferences to the second set of preferences, the data drift indicating that the preference group corresponds to the second set of preferences at the second time;
• automatically generating, based on the second set of preferences, second recommendation information for the user device;
• and
• sending, to the user device, the second recommendation information and one or more commands directing the user device to display the second recommendation information, wherein sending the one or more commands to the user device causes the user device to display the second recommendation information.

One or more non-transitory computer-readable media storing instructions that, when executed by a computing platform comprising at least one processor, a communication interface, and memory, cause the computing platform to:

• train, using historical preference information, a collaborative recommendation engine, wherein training the collaborative recommendation engine configures the collaborative recommendation engine to output recommendation information based on:
• historical user preference information of various user groups, and
• data drift of the historical preference information for each of the various user groups;
• receive, at a first time, an account access request from a user device;
• identify, using the collaborative recommendation engine, a preference group for the user device, wherein identifying the preference group is based on a similarity of preferences between the preference group and a user of the user device, and wherein the preference group corresponds to a first set of preferences at the first time;
• provide, to the user device and based on the first set of preferences, first recommendation information;
• receive, at a second time later than the first time, a second account access request from the user device;
• identify, using the collaborative recommendation engine, the preference group and data drift corresponding to the preference group between the first time and the second time, wherein the data drift indicates that the preference group corresponds to a second set of preferences at the second time, and wherein identifying the data drift comprises:
• identifying a different preference group that previously corresponded to the first set of preferences;
• identifying that the different preference group transitioned from the first set of preferences to the second set of preferences;
• and
• automatically predicting, based on the transition of the different preference group from the first set of preferences to the second set of preferences, the data drift indicating that the preference group corresponds to the second set of preferences at the second time;
• automatically generate, based on the second set of preferences, second recommendation information for the user device;
• and
• send, to the user device, the second recommendation information and one or more commands directing the user device to display the second recommendation information, wherein sending the one or more commands to the user device causes the user device to display the second recommendation information.