Occupation similarity through bipartite graphs
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Abstract (arXiv)
Similarity between occupations is a crucial piece of information when making career decisions. However, the notion of a single and unified occupation similarity measure is more of a limitation than an asset. The goal of the study is to assess multiple explainable occupation similarity measures that can provide different insights into inter-occupation relations. Several such measures are derived using the framework of bipartite graphs. Their viability is assessed on more than 450,000 job transitions occurring in Slovenia in the period between 2012 and 2021. The results support the hypothesis that several similarity measures are plausible and that they present different feasible career paths. The complete implementation and part of the datasets are available at https://repo.ijs.si/pboskoski/bipartite_job_similarity_code.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 5 of its 36 references that are in the map. First posted on arXiv 17 Feb 2022.
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References · 5
- 2016The Mythos of Model Interpretabilitycited by 721
- 2021Job Posting-Enriched Knowledge Graph for Skills-based Matchingcited by 8
- 2020Skill-driven Recommendations for Job Transition Pathwayscited by 5
- 2017Improved Consistent Weighted Sampling Revisitedcited by 3
- 2019Adaptively selecting occupations to detect skill shortages from online job adscited by 1
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