Data processing method and apparatus for identifying classification to which data belongs
First Claim
1. A data processing method for identifying a classification to which data belongs, the data comprising a plurality of features at least some of which are common to a plurality of classifications, the method comprising the steps of:
- extracting the features of the data as sequential elements and sequentially inputting the sequential elements or groups of elements until the classification to which data belongs is identified;
for each element or group of elements, comparing the element or group of elements with predetermined probability values for elements or groups of elements of each classification to determine a probability with a specified confidence range that the element or group of elements belong to a classification;
accumulating the probabilities to form an accumulated probability for each classification; and
identifying a classification to which the data belongs from the accumulated probability if the accumulated probability reaches a predetermined probability threshold, and the accumulated probability for the classification is greater than the accumulated probabilities of each of the other classifications by a predetermined amount.
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Abstract
A data processing method and apparatus is described for identifying a classification to which data belongs where the data comprises a plurality of features at least some of which are common to a plurality of classifications. The features of the data are extracted as sequential elements which are sequentially input until the classification to which data belongs is identified. The elements are compared with predetermined probability values for the elements of each classification to determine a probability that the elements belong to a classification. The probabilities are accumulated to form an accumulated probability for each classification and a classification to which data belongs is identified from the accumulated probability.
117 Citations
57 Claims
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1. A data processing method for identifying a classification to which data belongs, the data comprising a plurality of features at least some of which are common to a plurality of classifications, the method comprising the steps of:
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extracting the features of the data as sequential elements and sequentially inputting the sequential elements or groups of elements until the classification to which data belongs is identified; for each element or group of elements, comparing the element or group of elements with predetermined probability values for elements or groups of elements of each classification to determine a probability with a specified confidence range that the element or group of elements belong to a classification; accumulating the probabilities to form an accumulated probability for each classification; and identifying a classification to which the data belongs from the accumulated probability if the accumulated probability reaches a predetermined probability threshold, and the accumulated probability for the classification is greater than the accumulated probabilities of each of the other classifications by a predetermined amount. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28)
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29. Data processing apparatus for identifying a classification to which data belongs, the data comprising a plurality of features at least some of which are common to a plurality of classifications, the apparatus comprising:
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an inputter and extractor, which extracts the features of the data as sequential elements and sequentially inputs the sequential elements until the classification to which the data belongs is identified; memory for storing predetermined probability values for elements or groups of elements of each classification; a comparator arranged to receive and sequentially compare each element or group of elements with said predetermined probability values for each classification to determine a probability that the element or group of elements belong to a classification; an accumulator that accumulates the probabilities to form an accumulated probability with a specified confidence range for each classification; and an identification processor that identifies a classification to which the data belongs from the accumulated probability, said identification processor being arranged to identify a classification as a classification to which the data belongs if the accumulated probability of the classification reaches a predetermined probability threshold and the accumulated probability for the classification is greater than the accumulated probabilities of each of the other classifications by predetermined amount. - View Dependent Claims (30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56)
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57. A computer usable medium having computer readable instructions stored therein for causing a processor in a data processing apparatus to process signals defining data comprising a plurality of features at least some of which are common to a plurality of classification to identify a classification to which the data belongs, the instructions comprising instructions for:
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extracting the features of the data as sequential elements and sequentially inputting the sequential elements or groups of elements until the classification to which data belongs is identified; for each element or group of elements, comparing the element or group of elements with predetermined probability values for elements or groups of elements of each classification to determine a probability with a specified confidence range that the element or group of elements belong to a classification; accumulating the probabilities to form an accumulated probability for each classification; and identifying a classification to which the data belongs from the accumulated probability if the accumulated probability reaches a predetermined probability threshold, and the accumulated probability for the classification is greater than the accumulated probabilities of each of the other classifications by a predetermined amount.
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Specification