Systems and methods for performing contextual classification using supervised and unsupervised training
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United States of America Patent
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Aug 11, 2015
Grant Date -
Jun 13, 2013
app pub date -
Oct 3, 2012
filing date -
Oct 3, 2011
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Abstract
Computerized systems and methods are disclosed for performing contextual classification of objects using supervised and unsupervised training. In accordance with one implementation, content reviewers may review training objects and submit supervised training data for preprocessing and analysis. The supervised training data may be preprocessed to identify key terms and phrases, such as by stemming, tokenization, or n-gram analysis, and form vectorized objects. The vectorized objects may be used to train one or more models for subsequent classification of objects. In certain implementations, preprocessing or training, among other steps, may be performed in parallel over multiple machines to improve efficiency. The disclosed systems and methods may be used in a wide variety of applications, such as article classification and content moderation.
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