TY - JOUR
T1 - Career path level estimation and skill qualification feedback from textual descriptions
AU - Duchanoy, Carlos A.
AU - Moreno-Armendáriz, Marco A.
AU - Calvo, Hiram
AU - Hernández-Ramos, Víctor E.
N1 - Publisher Copyright:
© 2020 - IOS Press and the authors. All rights reserved.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
KW - Project manager career path level
KW - natural language processing
KW - profile classification
KW - skill qualification estimation
KW - word embeddings
UR - http://www.scopus.com/inward/record.url?scp=85091107611&partnerID=8YFLogxK
U2 - 10.3233/JIFS-179909
DO - 10.3233/JIFS-179909
M3 - Artículo
AN - SCOPUS:85091107611
SN - 1064-1246
VL - 39
SP - 2497
EP - 2507
JO - Journal of Intelligent and Fuzzy Systems
JF - Journal of Intelligent and Fuzzy Systems
IS - 2
ER -