Using Deep Learning To Extract Knowledge From Job Descriptions

An alternative job description was created by replacing the job title "infrastructure engineer" with "person" and removing the two other references. Now we run the job title prediction model on both job descriptions and compare the resulting embeddings with the learned job title embeddings from the model using the cosine similarity. Given the fact that "Isuzu technician" was not part of the job titles in our training data set, the prediction "auto technician" makes sense. The following tables show the top 5 input patterns from all job descriptions of the test data set for several filters.