Measures the similarity between two sets by dividing the intersection by the union. Perfect for comparing shared vs unique content elements. Higher scores indicate more shared content overlap.
Calculates the cosine of the angle between two document vectors. Excellent for comparing text content regardless of document length. Values closer to 1 indicate very similar content themes.
Uses content hashing to detect exact or near-exact duplicate content blocks. Highly sensitive to copy-paste scenarios. Even small scores suggest potential plagiarism.
Uses AI models to understand meaning and context beyond keywords. Detects paraphrased or rewritten content that maintains similar meaning. High scores indicate conceptual similarity.
Identifies underlying topics and themes across content. Groups content by subject matter similarity. Higher scores indicate sites covering similar topic areas or categories.