What is Document Similarity?
A measure of how similar two or more documents are based on their content or embeddings.
More about Document Similarity:
Document Similarity evaluates the degree of similarity between documents using techniques like embeddings or traditional term-based approaches. This process is essential in tasks like knowledge retrieval, clustering, and retrieval augmentation pipelines.
By leveraging document similarity, systems can group related content, improve search relevance, and enhance applications like semantic search.
Frequently Asked Questions
How is document similarity calculated?
It is often computed using vector-based techniques like cosine similarity or by comparing term frequencies.
What are common use cases for document similarity?
Applications include duplicate detection, content recommendation, and document clustering.
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