REFERENCE DRIVEN NLP-BASED TOPIC CATEGORIZATION

原文（中文）

A method includes: obtaining a record including text narration; inputting the text narration into an NLP model; generating, by the NLP model, encoded narration based on the text narration; determining similarity index between the encoded narration and each of encoded reference topics; comparing similarity index between the encoded narration and each encoded reference topic to similarity threshold; and determining whether similarity index between the encoded narration and each encoded reference topic is equal to or greater than similarity threshold. When the similarity index is equal to or greater than the similarity threshold, a corresponding reference topic is added to a result group, and, when the similarity index is less than the similarity threshold, the corresponding reference topic is left out of the result group. The record is classified based on the reference topic included in the result group and corresponding to the encoded reference topic having greatest similarity index.