| CPC G06F 16/906 (2019.01) | 19 Claims |
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1. A method comprising:
identifying, by a central database system for each of a plurality of historical users, an action being performed by the historical user within a domain and a set of web pages viewed by the historical user while performing the action;
generating, by the central database system, a training data set comprising, for each of the plurality of historical users, the identified action and the set of web pages viewed while the action is being performed;
training, by the central database system, a cluster model using the training data set, the cluster model configured to predict a desired action to be performed by an acting user based on web pages viewed by the acting user;
applying, by the central database system, a machine-learned model to web pages viewed by a target user to predict a next web page to be viewed by the target user;
applying, by the central database system, the cluster model to the web pages viewed by the target user and the predicted next web page to be viewed by the target user to identify an action being performed by the target user;
in response to determining that an observed next web page viewed by the target user is unrelated to the identified action being performed by the target user:
modifying, by the central database system, an interface displayed to the target user to include a web element to direct the target user to the predicted next web page; and
retraining the cluster model in response to determining that the target user is performing a new action different from actions performed by the plurality of historical users.
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