Identification and rejection of meaningless input during natural language classification

Identification and rejection of meaningless input during natural language classification

A method for identifying data that is meaningless and generating a natural language statistical model which can reject meaningless input. The method can include identifying unigrams that are individually meaningless from a set of training data. At least a portion of the unigrams identified as being...

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Hauptverfasser: Balchandran, Rajesh, Boyer, Linda
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creator Balchandran, Rajesh
Boyer, Linda
description A method for identifying data that is meaningless and generating a natural language statistical model which can reject meaningless input. The method can include identifying unigrams that are individually meaningless from a set of training data. At least a portion of the unigrams identified as being meaningless can be assigned to a first n-gram class. The method also can include identifying bigrams that are entirely composed of meaningless unigrams and determining whether the identified bigrams are individually meaningless. At least a portion of the bigrams identified as being individually meaningless can be assigned to the first n-gram class.
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title Identification and rejection of meaningless input during natural language classification
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