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Personalized Employee Training Course Recommendation with Career Development Awareness

Published: 20 April 2020 Publication History

Abstract

As a major component of strategic talent management, learning and development (L&D) aims at improving the individual and organization performances through planning tailored training for employees to increase and improve their skills and knowledge. While many companies have developed the learning management systems (LMSs) for facilitating the online training of employees, a long-standing important issue is how to achieve personalized training recommendations with the consideration of their needs for future career development. To this end, in this paper, we propose an explainable personalized online course recommender system for enhancing employee training and development. A unique perspective of our system is to jointly model both the employees’ current competencies and their career development preferences in an explainable way. Specifically, the recommender system is based on a novel end-to-end hierarchical framework, namely Demand-aware Collaborative Bayesian Variational Network (DCBVN). In DCBVN, we first extract the latent interpretable representations of the employees’ competencies from their skill profiles with autoencoding variational inference based topic modeling. Then, we develop an effective demand recognition mechanism for learning the personal demands of career development for employees. In particular, all the above processes are integrated into a unified Bayesian inference view for obtaining both accurate and explainable recommendations. Finally, extensive experimental results on real-world data clearly demonstrate the effectiveness and the interpretability of DCBVN, as well as its robustness on sparse and cold-start scenarios.

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              cover image ACM Conferences
              WWW '20: Proceedings of The Web Conference 2020
              April 2020
              3143 pages
              ISBN:9781450370233
              DOI:10.1145/3366423
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              Published: 20 April 2020

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              Author Tags

              1. Employee training course recommendation
              2. Intelligent education
              3. Recommender system

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              April 20 - 24, 2020
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              • (2024)Prerequisite-Enhanced Category-Aware Graph Neural Networks for Course RecommendationACM Transactions on Knowledge Discovery from Data10.1145/364364418:5(1-21)Online publication date: 28-Feb-2024
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