Career recommendation system for scientific students based on ontologies

3Citations
Citations of this article
17Readers
Mendeley users who have this article in their library.

Abstract

Students are usually unaware of their own skills. They choose to follow the trend, rather than the proper pathway. Which negatively aects the professional sector, and the development of the country. Orienting students, and guiding them would oer considerable benefits. Building the appropriate student's profiles is the golden key for an accurate orientation. To do so, relying on the simple use of the grade point average (GPA) will not be sucient, and mislead the guidance. Instead, studying their personality and skills has to be done, in order to provide them with their reel orientation. The presented solution aims to orient students to the most suitable career, based on a mathematical model, valid for all education systems, and takes into account the trades trends and students capabilities.

References Powered by Scopus

Mining of massive datasets

1292Citations
N/AReaders
Get full text

Interest and Its Contribution as a Mental Resource for Learning

918Citations
N/AReaders
Get full text

Towards social user profiling: Unified and discriminative influence model for inferring home locations

295Citations
N/AReaders
Get full text

Cited by Powered by Scopus

COMPUTER-ASSISTED CAREER GUIDANCE TOOLS FOR STUDENTS’ CAREER PATH PLANNING: A REVIEW OF ENABLING TECHNOLOGIES AND APPLICATIONS

4Citations
N/AReaders
Get full text

SCA Advice System: Ontology Framework for a Computer Curricula Advice System Based on Student Behavior

0Citations
N/AReaders
Get full text

Ontologic design of software engineering knowledge area knowledge components

0Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Abdellah, A. M., Karim, A. M., & Hamid, S. (2019). Career recommendation system for scientific students based on ontologies. Advances in Science, Technology and Engineering Systems, 4(4), 29–41. https://doi.org/10.25046/aj040404

Readers over time

‘20‘21‘22‘23‘24036912

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 5

71%

Lecturer / Post doc 2

29%

Readers' Discipline

Tooltip

Computer Science 4

50%

Social Sciences 2

25%

Decision Sciences 1

13%

Arts and Humanities 1

13%

Save time finding and organizing research with Mendeley

Sign up for free
0