What it measures: Combines both the angle and magnitude of vectors into a single similarity score.
When to use: Recommendation systems, when you want to consider both direction and strength of preferences.
Math insight: Rewards vectors that point in the same direction AND have high magnitudes.
Example: User preferences where both the type of content and the strength of preference matter.
Range: -∞ to +∞ (higher values = more similar)
