nearduplicateMethoden
Near-duplicate methods refer to techniques for identifying items that are substantially similar but not identical in content. They are widely used in information retrieval, data cleaning, web indexing, and digital repositories to reduce redundancy, improve search quality, and prevent content sprawl. The focus is on detecting near-duplicates, where texts or items share high similarity despite minor edits, paraphrasing, or reformatting.
Common approaches combine feature extraction with similarity assessment. Shingling creates sequences of tokens or characters from
Systems typically follow a two-stage pipeline: a blocking or candidate-generation stage reduces the number of potential
Evaluation of near-duplicate methods uses labeled data to report precision, recall, and F1 scores, along with