Towards Job-Transition-Tag Graph for a Better Job Title Representation Learning

Understand

Works on learning job title representation are mainly based on \textit{Job-Transition Graph}, built from the working history of talents.

• However, since these records are usually messy, this graph is very sparse, which affects the quality of the learned representation and hinders further analysis.
• To address this specific issue, we propose to enrich the graph with additional nodes that improve the quality of job title representation.
• Specifically, we construct \textit{Job-Transition-Tag Graph}, a heterogeneous graph containing two types of nodes, i.e., job titles and tags (i.e., words related to job responsibilities or functionalities).