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A hierarchical similarity based job recommendation service framework for university students

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Abstract

When people want to move to a new job, it is often difficult since there is too much job information available. To select an appropriate job and then submit a resume is tedious. It is particularly difficult for university students since they normally do not have any work experience and also are unfamiliar with the job market. To deal with the information overload for students during their transition into work, a job recommendation system can be very valuable. In this research, after fully investigating the pros and cons of current job recommendation systems for university students, we propose a student profiling based re-ranking framework. In this system, the students are recommended a list of potential jobs based on those who have graduated and obtained job offers over the past few years. Furthermore, recommended employers are also used as input for job recommendation result re-ranking. Our experimental study on real recruitment data over the past four years has shown this method’s potential.

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Acknowledgements

This work was partially supported by the State Key Laboratory of Software Development Environment of China (SKLSDE-2015ZX-17), the National Natural Science Foundation of China (Grant No. 61472021), and the Fundamental Research Funds for the Central Universities.

Author information

Authors and Affiliations

  1. State Key Laboratory of Software Development Environment, Beihang University, Beijing, 100191, China

    Rui Liu, Wenge Rong, Yuanxin Ouyang & Zhang Xiong

  2. Engineering Research Center of Advanced Computer Application Technology, Ministry of Education, Beihang University, Beijing, 100191, China

    Rui Liu, Wenge Rong, Yuanxin Ouyang & Zhang Xiong

  3. School of Computer Science and Engineering, Beihang University, Beijing, 100191, China

    Rui Liu, Wenge Rong, Yuanxin Ouyang & Zhang Xiong

Authors
  1. Rui Liu
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  2. Wenge Rong
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  3. Yuanxin Ouyang
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  4. Zhang Xiong
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Corresponding author

Correspondence to Wenge Rong.

Additional information

Rui Liu is currently pursing his PhD in School of Computer Science and Engineering at Beihang University, China. He obtained his MS and BS both from Beihang University in 2004 and 2001, respectively. His current research area covers recommendation system, information retrieval and so on.

Wenge Rong is an associate professor at Beihang University, China. He received his PhD from University of Reading, UK in 2010; MSc from Queen Mary College, UK in 2003; and BS from Nanjing University of Science and Technology, China in 1996. He has many years of working experience as a senior software engineer in numerous research projects and commercial software products. His research area covers service computing, enterprise modelling, and information management.

Yuanxin Ouyang is an associate professor at Beihang University, China. She received her PhD and BS from Beihang University in 2005 and 1997, respectively. Her research area covers recommendation system, data mining, social networks, and service computing.

Zhang Xiong is a professor in School of Computer Science of Engineering of Beihang University, China, and director of the Advanced Computer Application Research Engineering Center of National Educational Ministry of China. He has published over 100 referred papers in inter national journals and conference proceedings and won a National Science and Technology Progress Award. His research interests include smart cities, knowledge management, information systems, intelligent transportation systems and so on.

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Liu, R., Rong, W., Ouyang, Y. et al. A hierarchical similarity based job recommendation service framework for university students. Front. Comput. Sci. 11, 912–922 (2017). https://doi.org/10.1007/s11704-016-5570-y

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  • DOI: https://doi.org/10.1007/s11704-016-5570-y

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