Abstract: This application provides a keyword extraction method. The method includes: receiving an information entity including a title and a text; performing word segmentation on the text, to obtain a plurality of candidate words; and performing character segmentation on the title corresponding to semantics of the text, to obtain a plurality of characters; sequentially inputting the plurality of candidate words to a keyword extraction model, to obtain an attention weight of each candidate word relative to each character; selecting, from the plurality of candidate words, a candidate word that appears in the title; determining an extraction threshold according to an attention weight of the selected candidate word relative to each character; and determining a keyword of the text of the information entity from the candidate words according to the extraction threshold. This application further provide a method for training a keyword extraction model, a computer device, and a storage medium.

Abstract: This application provides a keyword extraction method. The method includes: receiving an information entity including a title and a text; performing word segmentation on the text, to obtain a plurality of candidate words; and performing character segmentation on the title corresponding to semantics of the text, to obtain a plurality of characters; sequentially inputting the plurality of candidate words to a keyword extraction model, to obtain an attention weight of each candidate word relative to each character; selecting, from the plurality of candidate words, a candidate word that appears in the title; determining an extraction threshold according to an attention weight of the selected candidate word relative to each character; and determining a keyword of the text of the information entity from the candidate words according to the extraction threshold. This application further provide a method for training a keyword extraction model, a computer device, and a storage medium.