sametexts

Sametexts is a term used in information retrieval and digital text processing to refer to a collection of texts that share identical or substantially identical content across documents, versions, or formats. A sametexts set may consist of exact copies or near-duplicates, where the core wording remains the same but formatting, punctuation, metadata, or minor edits differ. The term is not universally standardized, but it is used to distinguish duplicated or highly overlapping content from original material.

In practice, identifying sametexts relies on content-based techniques rather than surface formatting. Common methods include cryptographic hashes for exact copies, and content-based fingerprints such as shingling and locality-sensitive hashing to detect near-duplicates despite small edits or reordering. Effective handling requires considering language, encoding, and structural differences.

Applications include improving search indexing by avoiding redundant results, facilitating copyright and licensing checks, and cleaning large corpora for analysis. In software development and data pipelines, sametexts can reduce storage requirements and speed up processing by removing redundant text; however, they can also obscure the diversity of sources and require careful governance.

See also near-duplicate detection, text deduplication, content fingerprinting, and plagiarism detection.