Selectively deleting clusters of conceptually related words from a generative model for text
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United States of America Patent
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Jan 25, 2011
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app pub date -
Feb 7, 2007
filing date -
Feb 7, 2007
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Abstract
One embodiment of the present invention provides a system that selectively deletes clusters of conceptually-related words from a probabilistic generative model for textual documents. During operation, the system receives a current model, which contains terminal nodes representing random variables for words and contains one or more cluster nodes representing clusters of conceptually related words. Nodes in the current model are coupled together by weighted links, so that if an incoming link from a node that has fired causes a cluster node to fire with a probability proportionate to a weight of the incoming link, an outgoing link from the cluster node to another node causes the other node to fire with a probability proportionate to the weight of the outgoing link. Next, the system processes a given cluster node in the current model for possible deletion. This involves determining a number of outgoing links from the given cluster node to terminal nodes or cluster nodes in the current model. If the determined number of outgoing links is less than a minimum value, or if the frequency with which the given cluster node fires is less than a minimum frequency, the system deletes the given cluster node from the current model.
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