Method and apparatus for measuring similarity between documents

Data processing: database and file management or data structures – Database design – Data structure types

Reexamination Certificate

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C707S793000, C707S793000

Reexamination Certificate

active

06917936

ABSTRACT:
A measure of similarity between a first sequence of symbols and a second sequence of symbols is computed. Memory is allocated for a computational unit for storing values that are computed using a recursive formulation that computes the measure of similarity based on matching subsequences of symbols between the first sequence of symbols and the second sequence of symbols. A processor computes for the computational unit the values for the measure of similarity using the recursive formulation within which functions are computed using nested loops. The measure of similarity is output by the computational unit to an information processing application.

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Huma Lodhi, John Shawe-Taylor, Nello Cristianini, and Christopher J. C. H. Watkins, “Text classification using string kernels”, in NeuroCOLT2 Technical Report Series NC-TR-2000-079, 2000.
Huma Lodhi, John Shawe-Taylor, Nello Cristianini, and Chrstopher J. C. H. Watkins, “Text classification using string kernels”, in Advances in Neural Information Processing Systems, pp. 563-569, Cambridge, MA, 2001.
Huma Lodhi, Craig Saunders, John Shawe-Taylor, Nello Cristianini, and Chris Watkins, “Text classification using string kernels”, in Journal of Machine Learning Research, 2:419-444, Feb. 2002.
Chris Watkins, “Dynamic Alignment Kernels”, in Technical Report CSD-TR-98-11, Department of Computer Science, Royal Holloway University of London, Jan. 1999.

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