AI resume Matching: higher quality for your hires

Artificial Intelligence in HR | May 15 th, 2022

For each new job position, an HR has to manage a substantial number of applications; the risk is that of losing skills in the analysis phase and discarding profiles potentially in line with research.

INDEX

1. The solution? JobArch Skills Matching: the semantic search engine
2. How does it work?

the solution? JobArch Skills Matching: the semantic search engine

In the Applicant Tracking System, JobArch skills matching technology allows you to read and catalog resumes and job offers, understand their meaning and sort search results automatically.

This AI HR tool indistinctly analyzes all candidate profiles through resume screening software, extracting and processing specific information relating to the work experience and skills acquired by the candidates.
In this way, even if the professional qualifications used in the presentation phase do not uniquely correspond to the roles sought, the semantic engine is able to establish a match between the skills of the resource and the characteristics sought by the company, thus optimizing the process of research and selection of resources and offering customers a significant advantage both in terms of quantity (streamlining the flow of operations in the candidate’s analysis phase) and quality.

how does it work?

The engine does not perform a simple search through keywords but performs a logical analysis of the text, identifying semantic relationships and possible connections between words and extrapolating concepts.

Once a job offer has been entered, the semantic reader attributes professional tags with the tasks that the profile sought will have to perform.

The candidates are then sorted according to the professional tags read within the CV, which will be compared with those of the job offer.
The system detects the candidate’s compatibility with the job offer, which is immediately visible in the profile preview.

Thanks to the support of AI and Machine Learning, JobArch team is able to work progressively to improve and strengthen the semantic engine, ensuring a more accurate association between candidates and job advertisements and thus allowing technology to process a huge amount of data in real time and work on the quality of the applications.

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