Document Similarity refers to the process of determining how alike two or more documents are based on their content. This can involve comparing text, images, or other data types to identify similarities in themes, topics, or language. Techniques such as cosine similarity and Jaccard index are commonly used to quantify these similarities. Applications of document similarity include search engines, which use it to rank results, and plagiarism detection tools, which identify copied content. By analyzing the degree of similarity, these systems can provide more relevant information and maintain content integrity across various platforms.