方法证据记录
Text Deduplication
Text deduplication is a corpus-quality pipeline that identifies and removes exact and near-duplicate documents from large text collections. Grounded in Andrei Broder's 1997 resemblance theory, it is widely used to improve dataset quality for machine learning model training, search engine indexing, and any downstream NLP task that assumes a non-redundant corpus.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Text Deduplication (Near-Duplicate Detection)
分类方法记录 · process-pipeline / text-mining
- Broder, A.Z. (1997). On the Resemblance and Containment of Documents. Compression and Complexity of SEQUENCES. · URL
- Lee, K. et al. (2022). Deduplicating Training Data Makes Language Models Better. ACL 2022. · URL
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