Regression-tree compressed feature vector machine for time-expiring inventory utilization prediction

A non-transitory computer-readable medium at an online computing system encoding instructions executable by a processor to:

• receive, at an online computing system associated with a booking accommodation application, a request for a price suggestion for a subject listing, the subject listing associated with a time-expiring inventory available to be booked by one of a plurality of clients of the online computing system;
• generate a corpus of training data points associated with the time-expiring inventory, the training data points comprising a plurality of prices and a plurality of times until expiration of the time-expiring inventory;
• train a regression tree model to compress the corpus of training data points into a generalized model, the generalized model configured to output a price curve for the time-expiring inventory that is applicable regardless of which night the price curve is applied to, the compressing of the corpus of training data points enabling the regression tree model to avoid generating a separate price curve for each selectable night;
• generate, using the regression tree model, the price curve for the time-expiring inventory for a given night;
• determine, based on the generated price curve, a price suggestion for the time-expiring inventory and the given night;
• and
• provide the determined price suggestion for display through a user interface of the booking accommodation application on a manager computing device.

A computer system comprising:

• one or more computer processors for executing computer program instructions;
• and
• a non-transitory computer-readable storage medium storing instructions executable by the one or more computer processors to perform steps comprising:
• receiving, at an online computing system associated with a booking accommodation application, a request for a price suggestion for a subject listing, the subject listing associated with a time-expiring inventory available to be booked by one of a plurality of clients of the online computing system;
• generating a corpus of training data points associated with the time-expiring inventory, the training data points comprising a plurality of prices and a plurality of times until expiration of the time-expiring inventory;
• training a regression tree model to compress the corpus of training data points into a generalized model, the generalized model configured to output a price curve for the time-expiring inventory that is applicable regardless of which night the price curve is applied to, the compressing of the corpus of training data points enabling the regression tree model to avoid generating a separate price curve for each selectable night;
• generating, using the regression tree model, the price curve for the time-expiring inventory for a given night;
• determining, based on the generated price curve, a price suggestion for the time-expiring inventory and the given night;
• and
• providing the determined price suggestion for display through a user interface of the booking accommodation application on a manager computing device.