Maaike H. T. de Boer, Erik Boertjes, Mike Wilmer, Steven Vethman, Ajaya Adhikari and Jok Tang (TNO, The Netherlands)

Many vacancy texts do not reach their full potential; vacancies are too generic, too specific, or biased. In this demo paper, we proposea research prototype that helps users to create a better vacancy text using AI techniques in the domain of Labor Market. The proposedvacancy text from the user is analysed using an function classifier, skill extractor, bias detector and skill overlap algorithm. TheCompetent database consisting of functions, descriptions and skills as well as an annotated set of Dutch vacancy texts are fed to the AItechniques. In a small user evaluation, we show that the prototype has potential to help users in their need to create better vacancytexts. In future work, we aim to test the tool with more participants and improve the different functionalities. NOTE: the demo only works with Dutch text

Please visit the demo, and/or go to the URL Skills Matching (tnodatalab.nl) (username: reviewer; password: Skater-Strongman-Cytoplast-Yen0)

Screenshot of the demo

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