Patent Document ID: 8380492
Application ID: 12775580

Base Claim:
1. A method of cleaning an electronic document, the method comprising: identifying at least one sentence in the electronic document; numerically representing features of the sentence to obtain a numeric feature representation associated with the sentence; inputting the numeric feature representation into a machine learning classifier, the machine learning classifier being configured to determine, based on each numeric feature representation, whether the sentence associated with that numeric feature representation is a bad sentence; and removing sentences determined to be bad sentences from the electronic document to create a cleaned document, wherein numerically representing features of the sentence to obtain a numeric feature representation associated with the sentence comprises: creating a part of speech feature vector representation by performing part of speech tagging on each word in the sentence and determining a unique number associated with each part-of-speech corresponding to each word in the sentence, each position in the part of speech feature vector representation indicating a frequency of occurrence of a part of speech tag; creating a rule vector feature representation by determining whether the sentence satisfies a plurality of predetermined rules, each position in the rule vector feature representation indicating whether the sentence satisfies a particular one of the plurality of predetermined rules; and obtaining the numeric feature representation by concatenating the part of speech feature vector representation and the rule vector feature representation.

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Claim 6:
6. The method of claim 1 further comprising, prior to identifying: training the machine learning classifier with training data, the training data including one or more electronic training documents and one or more sentence status labels which identify one or more bad sentences in the electronic training documents.