Analysis of entry behavior of students on job boards in Japan based on factorization machine considering the interaction among features

Job-hunting activities in Japan are different from those in other countries. The features of this are the simultaneous recruitment of new graduates, joining the company in April, and the use by most students of such resources as employment information websites. In recent years, website job boards fo...

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Autores principales:	Tomoya Sugisaki, Yuri Nishio, Kenta Mikawa, Masayuki Goto, Takashi Sakurai
Formato:	article
Lenguaje:	EN
Publicado:	Taylor & Francis Group 2021
Materias:	big data management information prediction factorization machines Engineering (General). Civil engineering (General) TA1-2040
Acceso en línea:	https://doaj.org/article/501abed886814222bc924cf3731a98d8
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spelling	oai:doaj.org-article:501abed886814222bc924cf3731a98d82021-11-04T15:51:57ZAnalysis of entry behavior of students on job boards in Japan based on factorization machine considering the interaction among features2331-191610.1080/23311916.2021.1988381https://doaj.org/article/501abed886814222bc924cf3731a98d82021-01-01T00:00:00Zhttp://dx.doi.org/10.1080/23311916.2021.1988381https://doaj.org/toc/2331-1916Job-hunting activities in Japan are different from those in other countries. The features of this are the simultaneous recruitment of new graduates, joining the company in April, and the use by most students of such resources as employment information websites. In recent years, website job boards for new graduates have provided Japanese students with assistance in finding companies for which they want to work. On these boards, students can bookmark companies that they are interested in before deciding to apply. After bookmarking, a company bookmarked by a user can examine the information again later. However, even if the students rate various companies, many of these bookmarks do not lead to job applications. In other words, this can be regarded as a lost opportunity for gaining job applications from the perspective of the company. It is important for companies to gain as many job applications as possible to be successful in their recruitment activities. Therefore, a method of analyzing the entry behavior of students on job boards using factorization machines is proposed. The model predicts whether a student will submit a job application to a company. The prediction is based on student attributes and activity information, as well as information about the companies that they are interested in, as input variables. The interactions between input variables are also considered in making the prediction. In addition, the method supports student job-hunting activities and company measures for targeting students. To clarify the proposed model, analytical experiments were conducted with actual data from a website job board for new graduates.Tomoya SugisakiYuri NishioKenta MikawaMasayuki GotoTakashi SakuraiTaylor & Francis Grouparticlebig datamanagement informationpredictionfactorization machinesEngineering (General). Civil engineering (General)TA1-2040ENCogent Engineering, Vol 8, Iss 1 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	big data management information prediction factorization machines Engineering (General). Civil engineering (General) TA1-2040
spellingShingle	big data management information prediction factorization machines Engineering (General). Civil engineering (General) TA1-2040 Tomoya Sugisaki Yuri Nishio Kenta Mikawa Masayuki Goto Takashi Sakurai Analysis of entry behavior of students on job boards in Japan based on factorization machine considering the interaction among features
description	Job-hunting activities in Japan are different from those in other countries. The features of this are the simultaneous recruitment of new graduates, joining the company in April, and the use by most students of such resources as employment information websites. In recent years, website job boards for new graduates have provided Japanese students with assistance in finding companies for which they want to work. On these boards, students can bookmark companies that they are interested in before deciding to apply. After bookmarking, a company bookmarked by a user can examine the information again later. However, even if the students rate various companies, many of these bookmarks do not lead to job applications. In other words, this can be regarded as a lost opportunity for gaining job applications from the perspective of the company. It is important for companies to gain as many job applications as possible to be successful in their recruitment activities. Therefore, a method of analyzing the entry behavior of students on job boards using factorization machines is proposed. The model predicts whether a student will submit a job application to a company. The prediction is based on student attributes and activity information, as well as information about the companies that they are interested in, as input variables. The interactions between input variables are also considered in making the prediction. In addition, the method supports student job-hunting activities and company measures for targeting students. To clarify the proposed model, analytical experiments were conducted with actual data from a website job board for new graduates.
format	article
author	Tomoya Sugisaki Yuri Nishio Kenta Mikawa Masayuki Goto Takashi Sakurai
author_facet	Tomoya Sugisaki Yuri Nishio Kenta Mikawa Masayuki Goto Takashi Sakurai
author_sort	Tomoya Sugisaki
title	Analysis of entry behavior of students on job boards in Japan based on factorization machine considering the interaction among features
title_short	Analysis of entry behavior of students on job boards in Japan based on factorization machine considering the interaction among features
title_full	Analysis of entry behavior of students on job boards in Japan based on factorization machine considering the interaction among features
title_fullStr	Analysis of entry behavior of students on job boards in Japan based on factorization machine considering the interaction among features
title_full_unstemmed	Analysis of entry behavior of students on job boards in Japan based on factorization machine considering the interaction among features
title_sort	analysis of entry behavior of students on job boards in japan based on factorization machine considering the interaction among features
publisher	Taylor & Francis Group
publishDate	2021
url	https://doaj.org/article/501abed886814222bc924cf3731a98d8
work_keys_str_mv	AT tomoyasugisaki analysisofentrybehaviorofstudentsonjobboardsinjapanbasedonfactorizationmachineconsideringtheinteractionamongfeatures AT yurinishio analysisofentrybehaviorofstudentsonjobboardsinjapanbasedonfactorizationmachineconsideringtheinteractionamongfeatures AT kentamikawa analysisofentrybehaviorofstudentsonjobboardsinjapanbasedonfactorizationmachineconsideringtheinteractionamongfeatures AT masayukigoto analysisofentrybehaviorofstudentsonjobboardsinjapanbasedonfactorizationmachineconsideringtheinteractionamongfeatures AT takashisakurai analysisofentrybehaviorofstudentsonjobboardsinjapanbasedonfactorizationmachineconsideringtheinteractionamongfeatures
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Analysis of entry behavior of students on job boards in Japan based on factorization machine considering the interaction among features

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