Vector Search Demonstration

What is Vector Search?

Vector Search (also called semantic search) represents text as numerical vectors in a multi-dimensional space. Similar documents are positioned close to each other in this space.

Key Concepts:

• Document Embeddings: Text is converted into numerical vectors (arrays of numbers)
• Vector Space: Documents exist as points in a multi-dimensional space
• Similarity: Measured by distance or angle between vectors
• Cosine Similarity: Measures the cosine of the angle between two vectors (ranges from -1 to 1, where 1 = identical)

Formula for Cosine Similarity:

similarity = (A · B) / (||A|| × ||B||)

Where A · B is the dot product and ||A|| is the magnitude (length) of vector A.

Interactive Demo