| CPC G06F 40/30 (2020.01) [G06F 18/24 (2023.01); G06F 40/216 (2020.01); G06V 10/40 (2022.01); G06V 30/153 (2022.01); G06V 30/274 (2022.01); G06V 30/40 (2022.01)] | 20 Claims |
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1. A method comprising:
obtaining, by a processor, a session text of a user;
calculating, by the processor, a feature vector based on the session text by:
identifying a word segment set corresponding to the session text, the word segment set comprising a plurality of word segments,
calculating a weight value for each of the plurality of word segments,
determining a word vector for each of the plurality of word segments,
determining a text vector corresponding to the session text based on the word vector of each of the plurality of word segments and corresponding weight values, and
using the feature vector as the text vector;
determining, by the processor, probabilities, based on the feature vector, that the session text belongs to a plurality of intent labels, the probabilities calculated using a hierarchal intent classification model comprising multiple classifiers associated with multiple tiers of a hierarchal intent system, the plurality of intent labels associated with levels in the hierarchal intent system, wherein the multiple classifiers are trained using user session text data labeled with the plurality of intent labels; and
determining, by the processor, a user intent to the session text based on the probabilities.
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