The Influence of Feature Selection on Job Clustering for an E-recruitment Recommender System-Reference-Cited by-同舟云学术

The Influence of Feature Selection on Job Clustering for an E-recruitment Recommender System

Published:2020 Issue: Volume: Page:176-187
ISSN:0302-9743
Container-title:Artificial Intelligence and Soft Computing
language:
Short-container-title:

Author:

Junior Joel J. S.,Vilasbôas Fabricio G.,de Castro Leandro N.

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-61534-5_16

Reference12 articles.

1. Yoon Kin Tong, D.: A study of e-recruitment technology adoption in Malaysia. Ind. Manag. Data Syst. 109(2), 281–300 (2009)

2. Capelli, P.: Making the most of on-line recruiting. Harvard Bus. Rev. 79(3), 139–148 (2001)

3. Faliagka, E., Tsakalidis, A., Tzimas, G.: An integrated e-recruitment system for automated personality mining and applicant ranking. Internet Res. 22(5), 551–568 (2012)

4. Mitra, P., Murthy, C.A., Pal, S.K.: Unsupervised feature selection using feature similarity. IEEE Trans. Pattern Anal. Mach. Intell. 24(3), 301–312 (2002)

5. Dash, M., Liu, H., Yao, J.: Dimensionality reduction of unsupervised data. In: 1997 Proceedings of Ninth IEEE International Conference on Tools with Artificial Intelligence (1997)

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