The author discusses approximate deduplication using Jaccard similarity and MinHash signatures. This method involves converting documents into feature sets and finding similarities between them. By using a small “signature” for each document, similarity can be approximated without examining the entire sets. The MinHash technique allows for efficient scaling and grouping of similar documents. The post explores the trade-offs between sensitivity, recall, and performance in this approach. The surprising aspect is the comparison to HyperLogLog, showing similarities in using hash functions for estimation. Overall, the author finds MinHash to be a clever algorithmic trick worth exploring for engineers.
https://blog.nelhage.com/post/fuzzy-dedup/