Session embeddings for summarizing activity

A system, comprising:

• one or more processors;
• and
• memory storing instructions that, when executed by the one or more processors, cause the system to:
• obtain a first sentence representing a first sequence of actions between a user and a set of jobs;
• apply a language model to token embeddings of a first set of tokens in the first sentence and position embeddings of token positions in the first sentence to produce a first set of output embeddings;
• combine the first set of output embeddings into a first session embedding that encodes the first sequence of actions;
• and
• output the first session embedding for use in characterizing job-seeking activity of the user.

A non-transitory computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method, the method comprising:

• obtaining a first sentence representing a first session with a user and a second sentence representing a second session with the user, wherein each of the first and second sessions comprises a sequence of actions performed by the user with an online system;
• applying a language model to token embeddings of a first set of tokens in the first sentence and position embeddings of token positions in the first sentence to produce a first session embedding for the first session, wherein the first session embedding comprises an output embedding generated by the language model from a classification token added to the first sentence;
• applying the language model to the token embeddings of a second set of tokens in the second sentence and the position embeddings of the token positions in the second sentence to produce a second session embedding for the second session;
• and
• outputting the first and second session embeddings for use in characterizing activity of the user.