Hirize Shorts #2: Using Deep Learning to Solve the Resume Parsing Puzzle

HR staff often need help with time-consuming and error-prone manual resume parsing. Deep learning can automate and improve the accuracy of resume parsing. Resume parsers use AI to identify patterns and extract information like names and job experience.

Benefits for HR professionals

• Automates and speeds up recruitment
• Reduces human error
• Saves time on manual data entry

Parsers work by

• Using neural networks and natural language processing (NLP)
• Breaking down text to understand and extract relevant details
• Text extraction involves discerning patterns and storing information efficiently
• Resume parsers face challenges with diverse resume formats and complex layouts
• Methods to create effective parsers
• Combine rule-based systems with NLP
• Employ OCR for text recognition in complex formats

Hirize Resume Parser utilizes deep learning, OCR, and NLP to offer

• Automated parsing
• High accuracy and speed
• A ready-to-use tool that bypasses the need for developing custom parsers
• Information extraction from resumes with deep learning
• Pulling structured data such as names, job titles, and work history from resumes
• Handling vast quantities of resumes quickly, unlike manual methods
• Neural networks to understand context, improving accuracy despite typos or uncommon terms

To build a model, one should

Study NLP and select neural network models like LSTMs

• Curate a training dataset, a critical and time-intensive step
• Organizations should adopt deep learning-powered parsers for more effective recruitment

The "Hirize Resume Parser" uses deep learning and NLP to automate and speed up the recruitment process by quickly converting resumes into structured data with high accuracy, eliminating the need for manual data entry.

Try Hirize today!