Automated nonparametric content analysis for information management and retrieval
AssigneePresident and Fellows of Harvard College
InventorsGary KING, Connor T. JERZAK, Anton STEZHNEV
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AssigneePresident and Fellows of Harvard College
InventorsGary KING, Connor T. JERZAK, Anton STEZHNEV
Estimating the term…
Embodiments of the invention utilize a feature-extraction approach and/or a matching approach in combination with a nonparametric approach to estimate the proportion of documents in each of multiple labeled categories with high accuracy. The feature-extraction approach automatically generates continuously valued text features optimized for estimating the category proportions, and the matching approach constructs a matched set that closely resembles a data set that is unobserved based on an observed set, thereby improving the degree to which the distributions of the observed and unobserved sets resemble each other.
A method of computationally estimating a proportion of data elements in a plurality of data categories, the method comprising:
2-20. (canceled)
Apparatus for computationally estimating a proportion of data elements in a plurality of data categories, the apparatus comprising:
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