Method and apparatus for talent-post matching and computer readable storage medium

An apparatus for talent-post matching, comprising:

• one or more processors;
• a storage device for storing one or more programs;
• wherein when the one or more programs are executed by the one or more processors, the one or more processors are caused to:
• determine a first resume feature on a word level according to a resume to be predicted;
• determine a first post feature on a word level according to a post;
• determine a second post feature by associating features in the first post feature with a plurality of first weights;
• determine a post feature by adding up a plurality of second post features of the post set with a plurality of second weights;
• set a plurality of third weights for features in the first resume feature according to a matching degree of the features in the first resume feature and the second post feature, associate the features in the first resume feature with the plurality of third weights, and determine the associated features as a second resume feature, in which the second resume feature represents a work experience in the resume to be predicted;
• determine a resume feature representing all work experiences in the resume to be predicted according to the second resume feature and the post feature;
• and
• predict, according to the post feature of the post and the resume feature, a matching degree between the resume to be predicted and the post by using a pre-trained predictive model which is trained according to training samples, the training samples comprising posts and resumes to be trained.

A non-transitory computer readable storage medium having stored thereon a computer program, wherein when the computer program is executed by a processor, the processor is cause to:

• determine a first resume feature on a word level according to a resume to be predicted;
• determine a first post feature on a word level according to a post;
• determine a second post feature by associating features in the first post feature set with a plurality of first weights;
• determine a post feature by adding up a plurality of second post features of the post set with a plurality of second weights;
• set a plurality of third weights for features in the first resume feature according to a matching degree of the features in the first resume feature and the second post feature, associate the features in the first resume feature with the plurality of third weights, and determine the associated features as a second resume feature, in which the second resume feature represents a work experience in the resume to be predicted;
• determine a resume feature representing all work experiences in the resume to be predicted according to the second resume feature and the post feature;
• and
• predict, according to the post feature of the post and the resume feature, a matching degree between the resume to be predicted and the post by using a pre-trained predictive model which is trained according to training samples, the training samples comprising posts and resumes to be trained.