Career path discovery through bipartite graphs

Boškoski, Pavle (author), Redek, Tjaša (author), Perne, Matija (author), Boshkoska, Biljana Mileva (author)

To address the complexity of career decision-making limitations, we propose a novel framework for calculating occupation similarity measures based on bipartite graphs constructed from public occupation-skills ontologies. The proposed occupation similarity measures were constructed exclusively utilising knowledge from the European standard classification of occupations (ESCO) ontology. The resulting occupation similarity measures are fully explainable and computationally efficient. Furthermore, they are effortlessly transferable across regions and countries. This approach allows us to tailor the similarity measures to the specific needs, preferences, and career status of job seekers, providing a more personalised and comprehensive view of potential career paths. Our validation using an extensive dataset of over 450,000 job transitions in Slovenia confirms the effectiveness of our approach, demonstrating the value of employing multiple occupation similarity measures over a single measure.

• Language: English
• Keywords: labour market, decision making, graphs, career decision-making, bipartite graphs, explainable similarity measures, occupation similarity
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: EF - School of Economics and Business
• Publication status: Published
• Publication version: Version of Record
• Year: 2024
• Number of pages: Str. 140-153
• Numbering: Vol. 33, no. S1
• PID: 20.500.12556/RUL-167624
• UDC: 331.108
• ISSN on article: 2116-7052
• DOI: 10.1080/12460125.2024.2354585
• COBISS.SI-ID: 196604163
• Publication date in RUL: 04.03.2025

Record is a part of a journal

• Title: Journal of decision systems
• Publisher: Taylor & Francis
• ISSN: 2116-7052
• COBISS.SI-ID: 521615897

Licences

• License: CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
• Link: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Description: The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.

Secondary language

• Language: Slovenian
• Keywords: trg dela, odločanje, grafi

Projects

• Funder: ARRS - Slovenian Research Agency
• Project number: J5-4575
• Name: Investicije kot ključ do izgradnje trajnostnega podjetja: izgradnja teoretičnega modela in multimetodološka empirična analiza

• Funder: ARRS - Slovenian Research Agency
• Project number: V5-2267
• Name: Vpliv umetne inteligence na trg dela: ekonomska analiza, zmanjševanje kompetenčnega razkoraka in zagotavljanje delovnopravne zaščite