Abstract: The invention provides efficient searching with fuzzy criteria in very large information systems. The technique of the present invention uses the Pigeonhole Principle approach. This approach can be utilized with different embodiments, but the most effective realization would be to amplify some already given intrinsic approximate matching capabilities, like those in the FuzzyFind method [1][2]. Considering the following problem, data to be searched is presented as a bit-attribute vector. The searching operation includes finding a subset of this bit-attribute vector that is within particular Hamming distance. Normally, this search with approximate matching criteria requires sequential lookup for the whole collection of the attribute vector. This process can be easily parallelized, but in very large information systems this still would be slow and energy consuming.

Abstract: The invention provides efficient searching with fuzzy criteria in very large information systems. The technique of the present invention uses the Pigeonhole Principle approach. This approach can be utilized with different embodiments. but the most effective realization would be to amplify some already given intrinsic approximate matching capabilities, like those in the FuzzyFind method [1][2]. Considering the following problem, data to be searched is presented as a bit-attribute vector. The searching operation includes finding a subset of this bit-attribute vector that is within particular Flamming distance. Normally, this search with approximate matching criteria requires sequential lookup for the whole collection of the attribute vector. This process can be easily parallelized, but in very large information systems this still would be slow and energy consuming.