Job description generation based on machine learning

Abstract

Techniques are described for automatically generating job descriptions. Job categories are identified for the documents in the job description dataset based on clustering the documents. Sections within each document in the job description dataset are automatically identified, and each identified section is automatically classified. Each type of section is analyzed independently of the other section types using natural language processing, which allows automatic generation of each section of a new job description based on the section-specific data derived from the dataset. Section- and category-specific selective phrases are identified within the job description dataset, and embeddings are generated for the identified selective phrases. A request to generate a new job description for a particular category is received. For each section of new job description, the selective phrase embeddings for the section and for the identified category are used to identify phrases to include within the section of the job description.