<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>With the rapid development of the market economy, a large number of enterprises provide many jobs with different requirements. In the traditional application process, college students need to search the job requirements of each company one by one to match their own needs and conditions, which not only requires a lot of time and opportunity costs, but also has poor matching degree. This paper uses the recommendation and machine learning algorithms to match and optimise the job characteristics and needs according to the professional type, interest and specialty, employment area and personal preference of college students through the algorithm, and recommends suitable positions for college students to improve their success in application and increase their employment satisfaction rate.</p>
</abstract>

With the rapid development of the market economy, a large number of enterprises provide many jobs with different requirements. In the traditional application process, college students need to search the job requirements of each company one by one to match their own needs and conditions, which not only requires a lot of time and opportunity costs, but also has poor matching degree. This paper uses the recommendation and machine learning algorithms to match and optimise the job characteristics and needs according to the professional type, interest and specialty, employment area and personal preference of college students through the algorithm, and recommends suitable positions for college students to improve their success in application and increase their employment satisfaction rate.

Research on personalised recommendation algorithm for college students’ employment

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

With the rapid development of the market economy, a large number of enterprises provide many jobs with different requirements. In the traditional application...

Research on personalised recommendation algorithm for college students’ employment

Pubblicato online: 10 apr 2023

Pagine: 1143 - 1154

Ricevuto: 08 giu 2022

Accettato: 07 ago 2022

DOI: https://doi.org/10.2478/amns.2021.2.00234

Parole chiave
Employment of college students, recommendation algorithm, job demand, personalised demand

© 2023 Wenle Li, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on personalised recommendation algorithm for college students’ employment

Pubblicato online: 10 apr 2023

Pagine: 1143 - 1154

Ricevuto: 08 giu 2022

Accettato: 07 ago 2022

DOI: https://doi.org/10.2478/amns.2021.2.00234

Parole chiaveEmployment of college students, recommendation algorithm, job demand, personalised demand

© 2023 Wenle Li, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Parole chiave
Employment of college students, recommendation algorithm, job demand, personalised demand