Confusion and Countermeasures of College Students’ Career Guidance Work Based on Deep Learning Models-Reference-Cited by-同舟云学术

Confusion and Countermeasures of College Students’ Career Guidance Work Based on Deep Learning Models

Published:2023-11-13 Issue:1 Volume:9 Page:
ISSN:2444-8656
Container-title:Applied Mathematics and Nonlinear Sciences
language:en
Short-container-title:

Author:

Ji Liya¹

Affiliation:

1. 1 Intelligent Manufacturing College, Yangzhou Polytechnic Institute , Yangzhou , Jiangsu , , China .

Abstract

Abstract In this paper, we identify teaching signals and employment factors by designing a college student employment guidance work model. The deep learning model is used to identify the given feature vectors, find the word sequence with the highest probability among them, generate the probability of the corresponding acoustic feature vectors, and model the college students’ employment guidance work model to model and calculate them. The teaching signal feature distribution is used to create the description, and the output probability is adjusted to it. The number of college graduates in 2020 will be 6.3 million, an increase of 190,000 compared to last year, and the initial employment rate is 91.07%. The deep learning model can effectively identify college students’ employment confusion, propose effective countermeasures and improve the employment rate.

Publisher

Walter de Gruyter GmbH

Subject

Applied Mathematics,Engineering (miscellaneous),Modeling and Simulation,General Computer Science

Link

https://www.sciendo.com/pdf/10.2478/amns.2023.2.01115

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