1. A method comprising: executing instructions via a processor of a computing system for: generating a language model according to an approximate hashing technique, the language model comprising a plurality of event sequences in a target language, each member of the plurality of the event sequences associated with at least one count, the language model comprising a set of data structures organized in a hierarchy with lower levels corresponding to event sequences occurring less frequently being stored using fewer bits, the hierarchy having three or more levels; querying the language model for a member of the plurality of event sequences; and determining a probability associated with the member of the plurality of event sequences based on results of the query.
1. A method comprising: executing instructions via a processor of a computing system for: generating a language model according to an approximate hashing technique, the language model comprising a plurality of event sequences in a target language, each member of the plurality of the event sequences associated with at least one count, the language model comprising a set of data structures organized in a hierarchy with lower levels corresponding to event sequences occurring less frequently being stored using fewer bits, the hierarchy having three or more levels; querying the language model for a member of the plurality of event sequences; and determining a probability associated with the member of the plurality of event sequences based on results of the query. 3. The method of claim 1 , wherein the approximate hashing technique comprises generating a Stratified Spectral Bloom filter comprising a plurality of levels, each of the levels including a Spectral Bloom filter.