| 摘要 |
Text is classified by determining text features from the text, and transforming the text features to topic features. Scores are determined for each topic features using a discriminative topic model. The model includes a classifier that operates on the topic features, wherein the topic features are determined by the transformation from the text features, and the transformation is optimized to maximize the scores of a correct class relative to the scores of incorrect classes. Then, a class label with a highest score is selected for the text. In situations where the classes are organized in a hierarchical structure, the discriminative topic models apply to classes at each level conditioned on previous levels and scores are combined across levels to evaluate the highest scoring class labels.
|
