• Subscribe

iSGTW Feature - JobGrid connects Chinese graduates with employers

Feature - JobGrid connects Chinese graduates with employers

Schematic of JobGrid workflow.
Image courtesy of Feng Zhou, HUST.

Graduates from over 75 universities in China and their potential employers have a new tool to help them find each other: JobGrid.

Developed by researchers at Huazhong University of Science and Technology (HUST) and Beihang University (BUAA) on a grant from the Ministry of Education of China, JobGrid is the first data grid to provide an authentic, secure, user-friendly communication and decision support platform linking universities, graduates, companies and the government in China. It runs on the China Education and Research Network (CERNET).

JobGrid integrates students' records and relevant personal information from participating Chinese colleges and universities. It converts the dissimilar data to a uniform format, creating a comprehensive, authoritative database with privacy controls. The database supports data storage, extraction and export. Centralized transaction processing handled by a distributed data driver ensures consistent and efficient data access, management, and monitoring.

Graduating students can easily find their academic records and submit their resume and personal information.

"I learned about the JobGrid from the Employment Division of BUAA in September last year," says Chunmin Xu who graduated with a Masters degree from BUAA. "I decided to try to log in and publish my resume. Several days later, Beijing Watchdata System Co. Ltd. sent me an email. They said they had seen my resume and information through JobGrid, and invited me for an interview. I got the job!"

Chunmin Xu at graduation.

Image courtesy of Chunmin Xu and Feng Zhou.

In performance tests for time-intensive transactions, JobGrid performed well. Data conversion and export of a megabyte of student records took under 2 seconds, a distributed fuzzy search (in which search results are based on likely relevance, not on an exact match to criteria) of data from 75 universities took less than 10s, and the collection of dynamic monitoring information from 56 grid nodes on CERNET took under 100ms.

The team started development of GridJob in March 2007. By the end of that year already 73 colleges and universities had participated in system training at Wuhan, most of which had also completed their server configuration. Participation has been growing over the last months.

"There are almost 250,000 students using JobGrid," says Feng Zhao, one of the developers from HUST. "However, tracing and statistical tools are not yet designed in our system, so we have not measured exactly how many employers are using it and how many students have successfully found jobs. This is our future work."

They do know that over 65 colleges have collected basic student data, 56 colleges have registered on the JobGrid central server, and almost 50 colleges and universities have successfully completed the basic student data upload. As of mid-September 2008, JobGrid held university-supplied information for over 265,000 students, and employment information for almost 250,000.

-Feng Zhao, BUAA, and Anne Heavey, iSGTW

The development team includes Feng Zhao , Xiaoxing Sun, Hai Jin, and Song Wu from HUST and Bin Zhou from BUAA.

Join the conversation

Do you have story ideas or something to contribute? Let us know!

Copyright © 2023 Science Node ™  |  Privacy Notice  |  Sitemap

Disclaimer: While Science Node ™ does its best to provide complete and up-to-date information, it does not warrant that the information is error-free and disclaims all liability with respect to results from the use of the information.


We encourage you to republish this article online and in print, it’s free under our creative commons attribution license, but please follow some simple guidelines:
  1. You have to credit our authors.
  2. You have to credit ScienceNode.org — where possible include our logo with a link back to the original article.
  3. You can simply run the first few lines of the article and then add: “Read the full article on ScienceNode.org” containing a link back to the original article.
  4. The easiest way to get the article on your site is to embed the code below.