In this blog series, international experts on the topic of analyzing online job advertisements present their work. The presentations were given at the 7th OJA Forum, which is jointly organized twice a year by the Federal Institute for Vocational Education and Training and the Bertelsmann Stiftung. Topics at the 7th OJA Forum included the visualization and use of data using dashboards and the assignment of job titles to online job advertisements using various methodological approaches. This article is about the contribution of Rahkakavee Baskaran from &effect.

Leveraging Semantic Search with BERT: Classifying German Job Titles using the KLDB

This talk demonstrates a semantic search approach for classifying German job titles from online job advertisements using KldB (german classification of occupations). The algorithm is based on a BERT model (Bidirectional Encoder Representations from Transformers). The classification has an accuracy of 0.86 and a macro f1 value of 0.70 on the five digits of the KldB classification. In her presentation, Rahkakavee Baskaran explains the process from data pre-processing to model development and highlights the challenges encountered and insights gained.

 

Further contributions to „7th OJA Forum“:

7th OJA Forum (Part 1) – From data to knowledge on skills

7th OJA Forum (Part 2) – ESCWA’s Sills Monitor

7th OJA Forum (Part 3) – Enhancing the Employability of Students: a LMI Model using OJA

7th OJA Forum (Part 4) – Profession classification in the messy real world

7th OJA Forum (Part 5) – A Hybrid Methodology for Job Ad Title Normalization

7th OJA Forum (Part 6) – Semantic Search with BERT

7th OJA Forum (Part 7) – Explainable AI in OJA Analysis: Unveiling Job Level Classifier