Hi there
I am trying to build a resume shortlisting engine given a job description. Given that the job descriptions have information in form of sentences, it might yield a good embedding representation. However information within resumes is not much detailed, for e.g. skills delimited by comma mentioned within the Skills section. How can such limitation be addressed?
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You can write some examples about the format of the output. In other words, the model can learn how to provide the output, based on your guidelines.
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What have you tried? Do you have a corpus of resumes and job postings?
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Hiya -
Technical Recruiter here… this has been an issue since keyword Boolean searches have been standard. Adding a human layer to validate or perhaps compelling the submitter to provide context might be a path to a useful tool.
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