Semantic Matching

Semantic matching uses AI to understand the meaning and context of text, enabling matching based on concepts rather than just keyword overlap.

What is Semantic Matching?

Traditional keyword matching only finds exact text matches. If a job requires 'React' and a candidate lists 'React.js', keyword matching might miss the connection.

Semantic matching uses embeddings and language models to understand that 'React.js' equals 'React', that 'Python developer' is related to 'data science', and that '5 years experience' might satisfy '3+ years required'. This contextual understanding dramatically improves match quality.

Key Points

Understands meaning, not just keywords
Recognizes skill relationships
Handles synonyms automatically
Improves match quality
Reduces false negatives

Related Products

RecruitAI products that use semantic matching

Frequently Asked Questions

Why is semantic matching better than keyword matching?

Keyword matching misses qualified candidates who use different terminology. Semantic matching understands that 'frontend engineer' relates to 'React developer' even without keyword overlap.

See RecruitAI in action

Book a demo and learn how our AI APIs can transform your recruiting.