Career path level estimation and skill qualification feedback from textual descriptions

Issue title: Special section: Selected papers of LKE 2019

Guest editors: David Pinto, Vivek Singh and Fernando Perez

Article type: Research Article

Authors: Duchanoy, Carlos A.^{a; b} | Moreno-Armendáriz, Marco A.^b | Calvo, Hiram^{b; *} | Hernández-Ramos, Víctor E.^b

Affiliations: [a] Cátedra CONACyT, Centro de Investigación en Computación, Instituto Politécnico Nacional.Av. J.D. Bátiz e/M.O. de Mendizábal, Nva. Ind. Vallejo. 07738, Mexico City, Mexico | [b] Centro de Investigación en Computación, Instituto Politécnico Nacional.Av. J.D. Bátiz e/M.O. de Mendizábal, Nva. Ind. Vallejo. 07738, Mexico City, Mexico

Correspondence: [*] Corresponding author. Hiram Calvo, Centro de Investigación en Computación, Instituto Politécnico Nacional. Av. J.D. Bátiz e/M.O. de Mendizábal, Nva. Ind. Vallejo. 07738, Mexico City, Mexico. E-mail: [email protected].

Abstract: LinkedIn is a social medium oriented to professional career handling and networking. In it, users write a textual profile on their experience, and add skill labels in a free format. Users are able to apply for different jobs, but specific feedback on the appropriateness of their application according to their skills is not provided to them. In this work we particularly focus on applicants of the project management branch from information technologies—although the presented methodology could be extended to any area following the same mechanism. Using the information users provide in their profile, it is possible to establish the corresponding level in a predefined Project Manager career path (PM level). 1500+ experiences and skills from 300 profiles were manually tagged to train and test a model to automatically estimate the PM level. In this proposal we were able to perform such prediction with a precision of 98%. Additionally, the proposed model is able to provide feedback to users by offering a guideline of necessary skills to be learned to fulfill the current PM level, or those needed in order to upgrade to the following PM level. This is achieved through the clustering of skill qualification labels. Results of experiments with several clustering algorithms are provided as part of this work.

Keywords: Project manager career path level, profile classification, skill qualification estimation, natural language processing, word embeddings

DOI: 10.3233/JIFS-179909

Journal: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 2, pp. 2497-2507, 2020