A Bloom filter, conceived by Burton Howard Bloom in 1970, is a space-efficient probabilistic data structure that is used to test whether an element is a member of a set. False positive retrieval results are possible, but false negatives are not; i.e. a query returns either "inside set (may be wrong)" or "definitely not in set". Elements can be added to the set, but not removed (though this can be addressed with a counting filter). The more elements that are added to the set, the larger the probability of false positives.
Read more about Bloom Filter: Algorithm Description, Space and Time Advantages, Probability of False Positives, Interesting Properties, Examples, Alternatives
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“The true use of Shakespeare or of Cervantes, of Homer or of Dante, of Chaucer or of Rabelais, is to augment one’s own growing inner self.... The mind’s dialogue with itself is not primarily a social reality. All that the Western Canon can bring one is the proper use of one’s own solitude, that solitude whose final form is one’s confrontation with one’s own mortality.”
—Harold Bloom (b. 1930)