7. A method for minimizing hardware resources necessary to execute multi-domain membership tests by using a single bloom filter, the method comprising: receiving, by one or more processors, a set membership test request comprising one or more data items to search for and a dataset in which to search for the data items; performing, by one or more processors, multi-domain semantic analysis on the dataset to produce semantic information for the dataset, wherein the semantic information includes an indication of two or more domains present with respect to the received dataset; processing, by one or more processors, semantic information for the dataset to provide at least two complementary domain adaptive sets corresponding to the dataset; processing, by one or more processors, the at least two complementary domain adaptive sets to provide a multi-fractal representation of the dataset; applying a single bloom filter to the multi-fractal representation of the dataset to provide at least two filtered domain adaptive sets; processing, by one or more processors, the at least two filtered domain adaptive sets to provide a bijective holomorphic map of the two filtered domain adaptive sets; processing, by one or more processors, the bijective holomorphic map of the at least two filtered domain adaptive sets to provide a multi-domain insight aggregator corresponding to the dataset, wherein the multi-domain insight aggregator is a data structure that is processed using a single bloom filter to determine the presence of a data item across two or more domains; and determining, by one or more processors, whether the one or more data items are in the dataset according to the multi-domain insight aggregator.
8. The method of claim 7 , wherein the at least two complementary domain adaptive sets include a domain adaptive Julia set which corresponds to a Julia set matrix.