IDENTIFICATION OF ATTRIBUTES AND VALUES USING MULTIPLE CLASSIFIERS
First Claim
1. A method for at least one processing device to identify at least one attribute and at least one value in a body of text comprising a plurality of unknown attributes and a plurality of unknown values, the method comprising:
- labeling, by a first classification sub-component operating on a first portion of the body of text and implemented by the at least one processing device, a first portion of the plurality of unknown values as a first set of values;
labeling, by a second classification sub-component operating on a second portion of the body of text and implemented by the at least one processing device, a portion of the plurality of unknown attributes as a set of attributes and a second portion of the plurality of unknown values as a second set of values; and
updating, by the first classification sub-component and the second classification sub-component, learning models implemented by the first classification sub-component and the second classification sub-component based on the set of attributes and the first and second set of values.
1 Assignment
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Accused Products
Abstract
A body of text comprises a plurality of unknown attributes and a plurality of unknown values. A first classification sub-component labels a first portion of the plurality of unknown values as a first set of values, whereas a second classification sub-component labels a portion of the plurality of unknown attributes as a set of attributes and a second portion of the plurality of unknown values as a second set of values. Learning models implemented by the first and second classification subcomponents are updated based on the set of attributes and the first and second set of values. The first classification sub-component implements at least one supervised classification technique, whereas the second classification sub-component implements an unsupervised and/or semi-supervised classification technique. Active learning may be employed to provide at least one of a corrected attribute and/or corrected value that may be used to update the learning models.
41 Citations
18 Claims
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1. A method for at least one processing device to identify at least one attribute and at least one value in a body of text comprising a plurality of unknown attributes and a plurality of unknown values, the method comprising:
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labeling, by a first classification sub-component operating on a first portion of the body of text and implemented by the at least one processing device, a first portion of the plurality of unknown values as a first set of values; labeling, by a second classification sub-component operating on a second portion of the body of text and implemented by the at least one processing device, a portion of the plurality of unknown attributes as a set of attributes and a second portion of the plurality of unknown values as a second set of values; and updating, by the first classification sub-component and the second classification sub-component, learning models implemented by the first classification sub-component and the second classification sub-component based on the set of attributes and the first and second set of values. - View Dependent Claims (2, 3, 4, 5, 6)
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7. An apparatus, comprising at least one processing device, operable to identify at least one attribute and at least one value in a body of text comprising a plurality of unknown attributes and a plurality of unknown values, comprising:
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a first classification sub-component, implemented by at least one processing device, operable to label, from a first portion of the body of text, a first portion of the plurality of unknown values as a first set of values; and a second classification sub-component, implemented by the at least one processing device, operable to label, from a second portion of the body of text, a portion of the plurality of unknown attributes as a set of attributes and a second portion of the plurality of unknown values as a second set values, wherein learning models implemented by the first classification sub-component and the second classification sub-component are updated based on the set of attributes and the first and second set of values. - View Dependent Claims (8, 9, 10, 11, 12)
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13. A computer-readable medium having stored thereon instructions that, when executed by a computer, cause the computer to:
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in a body of text comprising a plurality of unknown attributes and a plurality of unknown values, label, based on a first classification technique operating on a first portion of the body of text, a first portion of the plurality of unknown values as a first set of values; label, based on a second classification technique operating on a second portion of the body of text, a portion of the plurality of unknown attributes as a set of attributes and a second portion of the plurality of unknown values as a second set of values; and update learning models used to implement the first classification technique and the second classification technique based on the set of attributes and the first and second set of values. - View Dependent Claims (14, 15, 16, 17, 18)
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Specification