Generating universal web profiles from diverse event data using generative artificial intelligence (ai) models

A system comprising:

• a processor;
• and
• a computer memory including instructions that, when executed by the processor, cause the system to carry out operations comprising:
• identifying a set of user events with text labels corresponding to user interactions from a set of users that includes a first user;
• converting the set of user events with the text labels into a set of embeddings;
• determining a subset of embeddings within a first embedding cluster;
• identifying a subset of text labels that are assigned to the subset of embeddings within the first embedding cluster;
• generating a topic name for the first embedding cluster based on the subset of text labels using a generative AI model;
• and
• based on determining a correlation in embedding space between the topic name and a subset of first user events, generating a user profile for the first user that includes the topic name.

A non-transitory computer-readable storage medium for determining topic names for user event signals using one or more generative artificial intelligence (AI) models, the non-transitory computer-readable storage medium storing instructions that, when executed by one or more processors, cause a computing device to perform operations comprising:

• converting a set of user events with text labels into a set of text embeddings;
• determining a subset of text embeddings within a first embedding cluster;
• identifying a subset of text labels that are assigned to the subset of text embeddings within the first embedding cluster;
• generating a topic name based on the subset of text labels using a generative AI model;
• and
• based on determining a correlation in embedding space between the topic name and a subset of first user events, generating a user profile for a first user that includes the topic name.