Description

Semantic similarity is a concept in natural language processing and information retrieval that quantifies how closely related two pieces of text are in terms of their meaning. It goes beyond simple lexical matching to capture the underlying semantic relationships between words, phrases, or documents. Various techniques, including distributional semantics and deep learning models, are used to compute semantic similarity. This concept is crucial for many NLP tasks, including information retrieval, text classification, and question answering.

Examples

• 🔄 Synonym detection
• 📑 Document clustering
• ❓ Question-answer matching

Applications