Patent ID: 11914963
Assignee: THETA LAKE, INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 9:
10. A method of semantically classifying electronic text, the method comprising:
storing a category in a computer memory, the category comprising a collection of semantic concepts, the collection of semantic concepts comprising a first semantic concept and a second semantic concept, each semantic concept in the collection of semantic concepts having an associated label and comprising a collection of semantically related words, sub-words, or phrases;
receiving, by a processor, a digital text to be evaluated against the category;
converting, by the processor, the digital text into a plurality of embedded text segments using an embedding;
converting, by the processor, the category into an embedded category comprising a plurality of embedded semantic concepts, said converting the category into the embedded category comprising embedding the collection of semantic concepts using the embedding;
determining, by the processor, a relatedness score for each of the plurality of embedded text segments with respect to each of the plurality of embedded semantic concepts to determine a plurality of relatedness scores;
determining, by the processor, that the digital text is related to the category based on the plurality of relatedness scores, the determining comprising comparing each relatedness score of the plurality of relatedness scores to a relatedness threshold for the collection of semantic concepts;
selecting a first semantic concept from the collection of semantic concepts for annotation based on the relatedness score corresponding to the first semantic concept satisfying the relatedness threshold;
based on a determination that the digital text is related to the category, annotating, by the processor, the digital text with the label of the first semantic concept of the category; and
storing, by the processor, the annotated digital text.