Systems and methods for classifying electronic information using advanced active learning techniques
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United States of America Patent
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Sep 1, 2015
Grant Date -
Sep 18, 2014
app pub date -
Mar 15, 2013
filing date -
Mar 15, 2013
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Abstract
Systems and methods for classifying electronic information or documents into a number of classes and subclasses are provided through an active learning algorithm. In certain embodiments, seed sets may be eliminated by merging relevance feedback and machine learning phases. In certain embodiments, the active learning algorithm forks a number of classification paths corresponding to predicted user coding decisions for a selected document. The active learning algorithm determines an order in which the documents of the collection may be processed and scored by the forked classification paths. Such document classification systems are easily scalable for large document collections, require less manpower and can be employed on a single computer, thus requiring fewer resources. Furthermore, the classification systems and methods described can be used for any pattern recognition or classification effort in a wide variety of fields.
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