Data processing: artificial intelligence – Knowledge processing system
Reexamination Certificate
2011-08-16
2011-08-16
Vincent, David R (Department: 2129)
Data processing: artificial intelligence
Knowledge processing system
Reexamination Certificate
active
08001069
ABSTRACT:
A method for finding sets of data (SDDs), which are similar to a target SDD, is invented. The method leverages a new category of signatures, called equivalence signatures, to characterize the SDDs and is applicable to all types of data that may be presented in two-dimensions. These signatures have the salient feature that, at worst, they change in a bounded manner when small changes are made to the SDDs and when used to find SDDs that are similar to a target SDDs, they allow for a significant reduction in the number of SDDs to be compared with the target. This is an improvement over the state of the art wherein the computational expensive process of performing a complete search against the entire corpus must be applied.
REFERENCES:
patent: 5442716 (1995-08-01), Otsu et al.
patent: 5933823 (1999-08-01), Cullen et al.
patent: 5956404 (1999-09-01), Schneier et al.
patent: 6096961 (2000-08-01), Bruti et al.
patent: 7031980 (2006-04-01), Logan et al.
patent: 7246314 (2007-07-01), Foote et al.
patent: 7725724 (2010-05-01), Ding et al.
patent: 7822700 (2010-10-01), Brooks
patent: 7849037 (2010-12-01), Brooks
patent: 7849038 (2010-12-01), Brooks
patent: 7849039 (2010-12-01), Brooks
patent: 7849040 (2010-12-01), Brooks
patent: 7849095 (2010-12-01), Brooks
patent: 2007/0198459 (2007-08-01), Boone et al.
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