What is the proportion of CVs, from the batch of different CVs, in which the education or experience section was parsed accurately?

The accuracy of Education and Experience parsing in RChilli Resume Parser varies depending on several factors, including:

• Resume format and structure

• Language and grammar used

• Document type (PDF, DOC, etc.)

• Use of tables, columns, or non-standard layouts

Our parser leverages advanced Natural Language Processing (NLP) and Deep Learning techniques to ensure high-quality extraction. However, due to the variability in resume styles and content, parsing performance may differ across different datasets.

While we strive to achieve optimal accuracy across all data points, the precise proportion of resumes where Education or Experience sections are parsed with complete accuracy is dataset-dependent and cannot be universally quantified without specific analysis.

If you are processing a batch of resumes and encounter issues or inconsistencies in parsing results, we encourage you to share a sample dataset with us. This allows our team to:

• Analyze the challenges

• Fine-tune our models if needed

• Offer targeted resolutions and suggestions

We are committed to continuous improvement and welcome your feedback to help enhance parsing performance.

For further assistance, please contact our support team by submitting through email at support@rchilli.com.