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I use them for natural language processing. There are cases where the performance increase is enormous (as in I wouldn't be able to afford the computation without them) and the downside of false positives is or can be made irrelevant.


Case in point, collocation detection over very large corpora:

https://github.com/RaRe-Technologies/bounter#example-on-the-...

Reduces RAM requirements some 31x times when automatically detecting common multiword expressions (e.g. "New York", "network license" or "Apache Hadoop"), which is significant.


Yep, I load an enormous list of lexemes (including multiword expressions) into a bloom filter and use it for text segmentation.




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