TY - JOUR
T1 - Occupation Recommendation with Major Programs for Adolescents
AU - Ochirbat, Ankhtuya
AU - Shih, Timothy K.
N1 - Publisher Copyright:
Copyright owned by the author(s) under the terms of the Creative Commons
PY - 2017
Y1 - 2017
N2 - Choosing a major in high school or undergraduate stage is an important decision in the person life. To find students’ majors as earlier as possible can help them to choose correct learning direction. Hence, it is essential to build a recommendation system that provides direction and guidance to students. In this regard, this study proposes Occupation Recommendation System with major program of study (ORS), a framework to assist students in the major/occupation selection, to provide the information about contemporary occupations, and to suggest the suitable occupations with major program of study based on their learning style, personality and vocational interests. Collaborative Filtering (CF) methods are employed, namely, a memory-based CF on vocational interest and a model-based CF on a regression model according to the learning style and the personality. The system provide top 10 occupations for each method respectively. This paper describes the architecture and interface of ORS and shows the experiments with 190 high school students. Moreover, comparisons between recommended majors, suggested majors by parents and students’ intended majors are made.
AB - Choosing a major in high school or undergraduate stage is an important decision in the person life. To find students’ majors as earlier as possible can help them to choose correct learning direction. Hence, it is essential to build a recommendation system that provides direction and guidance to students. In this regard, this study proposes Occupation Recommendation System with major program of study (ORS), a framework to assist students in the major/occupation selection, to provide the information about contemporary occupations, and to suggest the suitable occupations with major program of study based on their learning style, personality and vocational interests. Collaborative Filtering (CF) methods are employed, namely, a memory-based CF on vocational interest and a model-based CF on a regression model according to the learning style and the personality. The system provide top 10 occupations for each method respectively. This paper describes the architecture and interface of ORS and shows the experiments with 190 high school students. Moreover, comparisons between recommended majors, suggested majors by parents and students’ intended majors are made.
UR - http://www.scopus.com/inward/record.url?scp=85041514315&partnerID=8YFLogxK
M3 - 會議論文
AN - SCOPUS:85041514315
SN - 1824-8039
VL - 2017-March
JO - Proceedings of Science
JF - Proceedings of Science
T2 - 2017 International Symposium on Grids and Clouds, ISGC 2017
Y2 - 5 March 2017 through 10 March 2017
ER -