Sentiment prediction from textual data

  • US 8,682,649 B2
  • Filed: 11/12/2009
  • Issued: 03/25/2014
  • Est. Priority Date: 11/12/2009
  • Status: Active Grant
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First Claim
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1. A method to train data for sentiment prediction, comprising:

  • at a device comprising one or more processors;

    creating from a domain corpus a domain space that is a semantic representation of one or more identified areas of information;

    creating from affective data an affective space that is a semantic representation of a plurality of sentiments;

    generating a plurality of first affective anchors in the affective space, each first affective anchor corresponding to a respective sentiment in the affective space;

    mapping the plurality of first affective anchors generated in the affective space onto respective locations in the domain space, wherein the mapping of the first affective anchors is performed by the one or more processors;

    based on the respective locations to which the plurality of first affective anchors have been mapped in the domain space, generating a plurality of second affective anchors in the domain space, each second affective anchor corresponding to a respective sentiment in the domain space; and

    providing the domain space and the second affective anchors for predicting sentiment of text.

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