Professions API Reference🔗
Last update: February 2021
Introduction🔗
Textkernel's Professions API helps organizing job data according to established, international taxonomies of professions. It deals with spelling variations, synonyms and noise removal. Thus, it enables reliable analytics and effective matching of people and jobs.
Supported taxonomies🔗
Job titles can be mapped onto the following taxonomies:
- Textkernel's Profession Normalization Taxonomy (an established, cross-lingual, data-driven taxonomy)
- ISCO-2008
- KLDB-2020
- ONET-2019
- (Deprecated) ONET-2010
- (Deprecated) UK-SOC-2010
- UK-SOC-2020
- AMS
- UWV-BOC
Purposes of job normalization🔗
Normalizing job data to a taxonomy makes it possible to:
- Harmonize talent data from different sources and different languages
- Reliably compare data from different sources, for instance your talent pool versus market demand
- Match people and jobs based on a standard vocabulary, thereby increasing conversion
Technologies🔗
The Professions API uses:
- AI technology for understanding job titles and mapping them to taxonomy entries
- Knowledge Graph technology for representing relations between professions, industries, and job titles
Language support🔗
The following languages are supported as input (the job titles to be normalized):
de(German)en(English)es(Spanish)fr(French)it(Italian)ja(Japanese)nl(Dutch)pl(Polish)pt(Portuguese)zh(Chinese)
The normalized professions can be returned in the following languages:
de,de_CH(German)en,en_GB,en_US(English)es(Spanish)fr,fr_CH(French)it(Italian)ja(Japanese)nl(Dutch)pl(Polish)pt,pt_BR,pt_PT(Portuguese)zh(Chinese)