15. A system comprising: one or more computers configured to perform operations including: receiving a first collection of n-grams of a first natural language and a second collection of n-grams of a second natural language, the first and second collections of n grams being associated with one or more probabilities; using the first and second collections of n-grams and the associated probabilities to generate a plurality of randomized ranked collections of n-grams for each of the first natural language and the second natural language, each ranked collection of n-grams of the plurality of randomized ranked collection of n-grams having an ordering of n-grams according to a rarity of the n grams in the respective first collection and the second collection of n-grams; using each of the plurality of randomized ranked collections of n-grams to determine a plurality of signatures, each signature corresponding to a text of a collection of texts; and using the plurality of signatures to identify candidate text pairs within the collection of texts, the collection of texts including a plurality of texts in the first natural language and a plurality of texts in the second natural language.
17. The system of claim 15 , where generating a plurality of randomized ranked collections of n-grams further comprises: generating a probability matrix for each n-gram from the first and the second collections of n-grams using a first collection of text in the first natural language and a second collection of text in the second natural language, where the probability matrix for a particular n-gram identifies a probability for each of four categories: a probability that the n gram is not found in either the first or second collection of text, a probability that the n gram is found in the first collection of text but not the second collection of text; a probability that the n gram is found in the second collection of text but not the first collection of text, and a probability that the n-gram is found in both the first and second collection of text; and generating a ranked collection of n-grams for each of the first natural language and the second natural language as a function of the generated probability matrix for each n-gram of the respective natural language.