Personalized property recommender system using artificial reality and machine learning

A computer-readable storage medium storing instructions that, when executed by a computing system, cause the computing system to perform a process for generating personalized property recommendations using machine learning and artificial reality (XR), the process comprising:

• receiving factual data about one or more properties and user preferences comprising characteristics of a user preferred property;
• obtaining, via an XR system, experiential data indicative of a user's experience while the user was located at each of the one or more properties, wherein the experiential data comprises at least natural language spoken by the user while experiencing the one or more properties;
• predicting, by one or more natural language processing models using the natural language spoken by the user while experiencing each of the one or more properties, user favorability metrics associated with the properties, wherein at least one user favorability metric is predicted by:
• analyzing the experiential data for a first of the one or more properties to derive a property improvement prediction, the experiential data for the first property comprising user eye tracking data, wherein the analyzing correlates a) first natural language determined, by the one or more natural language processing models, to be indicative of property improvement with b) a target resolved from the user's eye tracking at a time of detection of the first natural language;
• and
• estimating a cost for the property improvement prediction;
• displaying, via the XR system, a virtual visualization that simulates the property improvement prediction;
• and
• generating, by one or more analytical models, a prioritized ranking of the one or more properties using the factual data about the one or more properties, the user preferences, and the predicted user favorability metrics.

A computing system for generating personalized property recommendations using machine learning and artificial reality (XR), the computing system comprising:

• one or more processors;
• and
• one or more memories storing instructions that, when executed by the one or more processors, cause the computing system to perform a process comprising:
• receiving factual data about one or more properties and user preferences comprising characteristics of a user preferred property;
• obtaining, via an XR system, experiential data indicative of a user's experience while the user was located at each of the one or more properties, wherein the experiential data comprises at least natural language spoken by the user while experiencing the one or more properties;
• predicting, by one or more natural language processing models using the natural language spoken by the user while experiencing each of the one or more properties, user favorability metrics associated with the properties, wherein at least one user favorability metric is predicted by:
• analyzing the experiential data for a first of the one or more properties to derive a property improvement prediction, the experiential data for the first property comprising user eye tracking data, wherein the analyzing correlates a) first natural language determined, by the one or more natural language processing models, to be indicative of property improvement with b) a target resolved from the user's eye tracking at a time of detection of the first natural language;
• and
• estimating a cost for the property improvement prediction;
• and
• generating, by one or more analytical models, a prioritized ranking of the one or more properties using the factual data about the one or more properties, the user preferences, and the predicted user favorability metrics.