ADAPTIVE DATA CLASSIFICATION FOR DATA MINING
First Claim
1. A method comprising:
- receiving input from a user defining a classification;
determining a sample set of unstructured data based on the classification defined by the user;
analyzing the sample set of unstructured data to determine a classification mapping that maps attributes of the sample set of unstructured data to class labels for the classification;
indexing attributes of a set of data objects in a second set of unstructured data;
mapping one or more data objects in the set of data objects to the class label based on the classification mapping that maps indexed attributes of the one or more data objects to the class label;
determining feedback based on the user'"'"'s response to an interaction with results determined using the class label; and
adapting the classification mapping based on an analysis of the feedback by adjusting the sample set used to determine the classification mapping to the class label.
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Accused Products
Abstract
A method and system for adaptive classification during information retrieval from unstructured data are provided. The method includes receiving input from a user defining a classification. A sample set of unstructured data based on the user defined classification defined is determined. The sample set of unstructured data is analyzed to determine a classification mapping that maps attributes of the sample set of unstructured data to class labels for the classification. The attributes of a set of data objects in a second set of unstructured data are indexed and one or more data objects in the set of data objects are mapped to the class label based on the classification mapping. Feedback based on the user'"'"'s response to an interaction with results is determined using the class label. Finally, adaptive classification mapping is performed based on analysis of feedback by adjusting the sample set of data objects.
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Citations
20 Claims
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1. A method comprising:
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receiving input from a user defining a classification; determining a sample set of unstructured data based on the classification defined by the user; analyzing the sample set of unstructured data to determine a classification mapping that maps attributes of the sample set of unstructured data to class labels for the classification; indexing attributes of a set of data objects in a second set of unstructured data; mapping one or more data objects in the set of data objects to the class label based on the classification mapping that maps indexed attributes of the one or more data objects to the class label; determining feedback based on the user'"'"'s response to an interaction with results determined using the class label; and adapting the classification mapping based on an analysis of the feedback by adjusting the sample set used to determine the classification mapping to the class label. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. An apparatus comprising:
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one or more processors; and logic encoded in one or more tangible media for execution by the one or more processors and when executed operable to; receive input from a user defining a classification; determine a sample set of unstructured data based on the classification defined by the user; analyze the sample set of unstructured data to determine a classification mapping that maps attributes of the sample set of unstructured data to class labels for the classification; index attributes of a set of data objects in a second set of unstructured data; map one or more data objects in the set of data objects to the class label based on the classification mapping that maps indexed attributes of the one or more data objects to the class label; determine feedback based on the user'"'"'s response to an interaction with results determined using the class label; and adapt the classification mapping based on an analysis of the feedback by adjusting the sample set used to determine the classification mapping to the class label. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17, 18)
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19. An apparatus comprising:
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means for receiving input from a user defining a classification; means for determining a sample set of unstructured data based on the classification defined by the user; means for analyzing the sample set of unstructured data to determine a classification mapping that maps attributes of the sample set of unstructured data to class labels for the classification; means for indexing attributes of a set of data objects in a second set of unstructured data; means for mapping one or more data objects in the set of data objects to the class label based on the classification mapping that maps indexed attributes of the one or more data objects to the class label; means for determining feedback based on the user'"'"'s response to an interaction with results determined using the class label; and means for adapting the classification mapping based on an analysis of the feedback by adjusting the sample set used to determine the classification mapping to the class label. - View Dependent Claims (20)
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Specification