Document Similarity

Document similarity focuses on quantifying the resemblance between textual documents, crucial for tasks like plagiarism detection, information retrieval, and recommendation systems. Current research emphasizes efficient algorithms, moving beyond quadratic-time complexities associated with transformer-based approaches by exploring sparse graph representations and specialized embeddings tailored to specific document aspects. These advancements aim to improve accuracy and scalability, particularly for large corpora and morphologically rich languages, impacting fields ranging from biomedical literature analysis to financial auditing.