Advertisement

TRaining AssigNment Service (TRANS) to Meet Organization Level Skill Need

  • Atul SinghEmail author
  • Rajasubramaniam T.
  • Gurulingesh Raravi
  • Koyel Mukherjee
  • Partha Dutta
  • Koustuv Dasgupta
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 255)

Abstract

The need for training employees in new skills in an organization generally arises due to the changing skill requirements coming from the introduction of new products, technology and customers. Efficient assignment of employees to trainings so that the overall training cost is minimized while considering the career goals of employees is a challenging problem and to the best of our knowledge there is no existing work in literature that solves this problem. This paper presents TRaining AssigNment Service (TRANS) that minimizes an organization’s overall training costs while assigning employees to trainings that match their learning ability and career goals. TRANS uses an ORGanization and Skills ontology (ORGS) to calculate the cost for training each available employee for a potential role taking into account constructivist learning theory. TRANS uses TRaining assIgnMent algorithm (TRIM), based on Hungarian method for bipartite matching, for assigning employees to trainings. In our experiments with real-world data, proposed allocation algorithm performs better than the existing strategy of the organization.

Keywords

Applications Training management system Learning theory Organization and skills ontology Training cost optimization 

References

  1. 1.
    Piskurich, G.M., Beckschi, P., Hall, B.: The ASTD Handbook of Training Design and Delivery: A Comprehensive Guide to Creating and Delivering Training Programs, Instructor-led, computer-Based, or Self-Directed. McGraw-Hill, New York (2000)Google Scholar
  2. 2.
    Kuhn, H.W.: The hungarian method for the assignment problem. Nav. Res. Logistics Q. 2(1–2), 83–97 (1955)MathSciNetCrossRefzbMATHGoogle Scholar
  3. 3.
    Olson, M.H., Hergenhahn, B.R.: An Introduction to Theories of Learning. Pearson/Prentice Hall, Upper Saddle River (2009)Google Scholar
  4. 4.
    Schunk, D.H.: Learning theories. Printice Hall Inc., New Jersey (1996)Google Scholar
  5. 5.
    W3C: The organization ontology (2014)Google Scholar
  6. 6.
    Brickley, D., Miller, L.: Foaf vocabulary specification 0.98. Namespace Document 9 (2012)Google Scholar
  7. 7.
    Schmidt, A., Kunzmann, C.: Towards a human resource development ontology for combining competence management and technology-enhanced workplace learning. In: On the Move to Meaningful Internet Systems: OTM Workshops (2006)Google Scholar
  8. 8.
    Schmidt, A., Kunzmann, C.: Sustainable competency-oriented human resource development with ontology-based competency catalogs. In: eChallenges (2007)Google Scholar
  9. 9.
    Fazel-Zarandi, M., Fox, M.S.: An ontology for skill and competency management. In: FOIS (2012)Google Scholar
  10. 10.
    Fazel-Zarandi, M., Fox, M.S.: Reasoning about skills and competencies. In: Camarinha-Matos, L.M., Boucher, X., Afsarmanesh, H. (eds.) PRO-VE 2010. IFIP AICT, vol. 336, pp. 372–379. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  11. 11.
    Sicilia, M.A.: Ontology-based competency management: infrastructures for the knowledge intensive learning organization. Europe 17 (2014)Google Scholar
  12. 12.
    Draganidis, F., Chamopoulou, P., Mentzas, G.: An ontology based tool for competency management and learning paths. In: 6th International Conference on Knowledge Management (2006)Google Scholar
  13. 13.
    Manouselis, N., Drachsler, H., Vuorikari, R., Hummel, H., Koper, R.: Recommender systems in technology enhanced learning. In: Ricci, F., Rokach, L., Shapira, B., Kantor, P.B. (eds.) Recommender Systems Handbook, pp. 387–415. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  14. 14.
    Shen, L., Shen, R.-M.: Learning content recommendation service based-on simple sequencing specification. In: Liu, W., Shi, Y., Li, Q. (eds.) ICWL 2004. LNCS, vol. 3143, pp. 363–370. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  15. 15.
    Malzahn, N., Ziebarth, S., Hoppe, H.U.: Semi-automatic creation and exploitation of competence ontologies for trend aware profiling, matching and planning. Knowl. Manage. E-Learn. Int. J. 5(1), 84–103 (2013)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Atul Singh
    • 1
    Email author
  • Rajasubramaniam T.
    • 1
  • Gurulingesh Raravi
    • 1
  • Koyel Mukherjee
    • 1
  • Partha Dutta
    • 1
  • Koustuv Dasgupta
    • 1
  1. 1.Xerox Research Centre IndiaBengaluruIndia

Personalised recommendations