AI-Based Syntactic Pattern Recognition of Sequences

This patent concerns the traditional problem encountered in the syntactic Pattern Recognition (PR) of strings or sequences. The primary investigator involved in this work is a Full Professor at Carleton University in Ottawa, Canada, and is a Fellow of the IEEE. The primary problem solved by the invention involves determining the string or sequence that is most similar to a sequence presented to the system. The search could be initiated by presenting, to the system, a noisy or inexact version of a string contained in memory for example, at a web-site or in the library or database. The invention will yield the closest string/sequence by searching the dictionary of possible words using a newly invented AIbased strategy. The core of this invention is this search strategy, called the Clustered Beam Search. Experiments have been done to show the benefits of the CBS over the current state-ofthe-art, and the results demonstrate an unbelievably marked improvement (sometimes as high as 90%) for large libraries and databases. The solution provided by the invention would be applicable in numerous areas including : Inexact or proximity searching on the Internet, keyword-based search in libraries and databases, spelling correction, speech and character recognition (including optical character recognition), and the processing of biological sequences, for example, in human genome projects. These applications are briefly described below. ∗This author can be addressed at: School of Computer Science, Carleton University, Ottawa, Canada : K1S 5B6. e-mail address : [email protected]. †Professor and Fellow of the IEEE. This author can be contacted at: School of Computer Science, Carleton University, Ottawa, Canada : K1S 5B6. e-mail address : [email protected]. More information about this inventor, who holds a Doctorate from Purdue University, can be found at www.scs.carleton.ca/∼oommen.