Classification and prediction of academic talent using data mining techniques

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

In talent management, process to identify a potential talent is among the crucial tasks and need highly attentions from human resource professionals. Nowadays, data mining (DM) classification and prediction techniques are widely used in various fields. However, this approach has not attracted much interest from people in human resource. In this article, we attempt to determine the potential classification techniques for academic talent forecasting in higher education institutions. Academic talents are considered as valuable human capital which is the required talents can be classified by using past experience knowledge discovered from related databases. As a result, the classification model will be used for academic talent forecasting. In the experimental phase, we have used selected DM classification techniques. The potential technique is suggested based on the accuracy of classification model generated by that technique. Finally, the results illustrate there are some issues and challenges rise in this study, especially to acquire a good classification model.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages491-500
Number of pages10
Volume6276 LNAI
EditionPART 1
DOIs
Publication statusPublished - 2010
Event14th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2010 - Cardiff
Duration: 8 Sep 201010 Sep 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume6276 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other14th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2010
CityCardiff
Period8/9/1010/9/10

Fingerprint

Data mining
Data Mining
Prediction
Human Resources
Forecasting
Personnel
Human Capital
Process Management
Higher Education
Education
Model

Keywords

  • Academic talent
  • Classification
  • Data mining (DM)
  • Prediction

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Jantan, H., Hamdan, A. R., & Ali Othman, Z. (2010). Classification and prediction of academic talent using data mining techniques. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (PART 1 ed., Vol. 6276 LNAI, pp. 491-500). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6276 LNAI, No. PART 1). https://doi.org/10.1007/978-3-642-15387-7_53

Classification and prediction of academic talent using data mining techniques. / Jantan, Hamidah; Hamdan, Abdul Razak; Ali Othman, Zulaiha.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 6276 LNAI PART 1. ed. 2010. p. 491-500 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6276 LNAI, No. PART 1).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Jantan, H, Hamdan, AR & Ali Othman, Z 2010, Classification and prediction of academic talent using data mining techniques. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 1 edn, vol. 6276 LNAI, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 6276 LNAI, pp. 491-500, 14th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2010, Cardiff, 8/9/10. https://doi.org/10.1007/978-3-642-15387-7_53
Jantan H, Hamdan AR, Ali Othman Z. Classification and prediction of academic talent using data mining techniques. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 1 ed. Vol. 6276 LNAI. 2010. p. 491-500. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). https://doi.org/10.1007/978-3-642-15387-7_53
Jantan, Hamidah ; Hamdan, Abdul Razak ; Ali Othman, Zulaiha. / Classification and prediction of academic talent using data mining techniques. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 6276 LNAI PART 1. ed. 2010. pp. 491-500 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).
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