METHOD AND APPARATUS FOR UNSUPERVISED LEARNING OF MULTI-RESOLUTION USER PROFILE FROM TEXT ANALYSIS
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United States of America Patent
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Issued Date -
Aug 14, 2014
app pub date -
Sep 28, 2012
filing date -
Sep 30, 2011
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Abandoned
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Abstract
A method and apparatus for retrieving information from a massive amount of user-written businesses reviews are described. From the bag of words of a given review set, a graph based on mutual information between the words is built. Spectral analysis on this graph enables creation of a Euclidean space specific to those reviews where the distance corresponds to semantic proximity. Applying a cover-tree based divisive hierarchical clustering in this space yields therefore a semantic tag tree. Such a taxonomy is specific of the review set used, which could be all the reviews about a product or written by a user, and can be used for profiling. These taxonomies are used to build profiles. Also described is a tool to summarize and browse the review set based on the obtained trees.
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