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Artificial Intelligence and Rules-Based Automation for Vetting Resumes

One of the biggest challenges that HR practitioners face today is finding suitable people to recruit. In the past, this task has proven to be challenging, in part because of inefficient manual tasks that hamper the recruitment process and the lack of access to the right details. In fact, 46% of employers and workplace managers described “finding the right candidate” as the biggest obstacle to recruiting today, based on research undertaken by LinkedIn.

To tackle these issues, new technologies have emerged in the HR tech ecosystem with robust solutions using Big Data, predictive analytics, and AI. These can help to automate and improve everything from job advertising to resume screening, scheduling and text recruitment in your recruitment process. These new instruments offer us ways to resolve the limitations and prejudices inherent in the recruitment of automated, market-related processes, complex metrics, and even budget constraints. This makes it easier for recruiters to select candidates who provide their resumes when applying for work.

Using an intelligent automation tool such as Gleematic, we can compare how to check resumes using various functions. The following are tips with names of functions in Gleematic A.I. Designer.

  1. The rules-based function: “If Variable” function under the “Variable” tab can be used to look for a keyword in the resumes based on a keyword list.
  2. The AI function: “Fuzzy Extract One” can be used to look for a keyword in the resumes based on a keyword list. It is found under the “Text Analytics” function.
  3. The AI function: “Text Classifier” can be used to look for a keyword in the resumes based on a keyword list. It is found under the “Text Analytics” function.
  4. The “If Variable in Variable” and “Text Classifier” functions may be more time-consuming to set up as there are functions required to clean up the data in the keywords list and resumes
  5. The “If Variable in Variable” does not allow for spelling errors or shortened spelling forms as compared to the “Text Classifier” and “Fuzzy Extract One”
  6. The “If Variable in Variable” and “Text Classifier” functions offer more customizability as the “Fuzzy Extract One” has a fixed algorithm
  7. “If Variable in Variable” requires more effort when looking for multiple keywords as there have to be more steps created and more sub-scripts selected within these steps.
  8. “Text Classifier” and “Fuzzy Extract One” allows for greater flexibility of what the list of keywords is
  9. “If Variable in Variable” and “Text Classifier” allows for sub-scripts to be run in between each keyword from the keywords list
  10. “Fuzzy Extract One” and “Text Classifier” are faster methods of doing the keyword matching as compared to “If Variable in Variable”. The technology behind these functions are more efficient

Those are some differences between A.I. and “non-A.I” functions for vetting resumes. You can read our other articles here.

Written by : Zachary

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