Data Enrichment & Classification – Professions & Skills Ontology
The best way to use clever data in your HR-work. Data Services by Actonomy offers the best-of-breed ontology on the HR-market, but without the searching and matching component offered by Actonomy xMP.
This is the recruitment technology for those who want to enrich (such as skills enrichment) their searching and matching software with the best HR-ontology on the market. These ontologies are available for more than 12 languages, such as English, German, Dutch, Spanish, French, Portugese, Italian, Swedish a.o, and contain detailed skill sets , job titles, soft skills, education, certifications, and much more HR-related information in a highly structured semantic knowledge network.
Actonomy’s ontologies go far beyond traditional taxonomies often used in searching and matching.
Actonomy’s ontology is unparalleled and consist of +1 000 000 000 titles and skills
Cross lingual professions & skills ontology for structured views on the labor market!
Proven in time
Several 100 Millions of job descriptions collected over 15 years and is one of the oldest HR ontologies in the world
How it works
Step 1: Data input
Start with uploading resumes, employee profiles or simply enter search queries
All knowledge starts with text input. Any type of input is possible: both résumés job profiles and corporate employee profiles are uploaded into the system, to be analyzed. Large amounts of data are entered: the more data, the better the quality of the resulting analyses will be.
Step 2: Text analyses & understanding
What does your input actually mean
Artificial intelligence will interpret the meaning and content of the uploaded text. Multiple CV languages are interpreted.
Step 3: The Professions and skills ontology
Updating from and to the ontology
All meanings, concepts, content are now added to the continuously expanding knowledge database, the ontology. The more data are uploaded, the smarter the ontology gets. As per today, Actonomy is owning the largest HR-ontology in the world (more than 1 billion entries).
Step 4: Enrichment & classification
How can we enrich the query and make it easy to retrieve
Meaning is added, words and concepts are classified in categories of concepts. By enriching the request, the system makes it easier to retrieve.
Step 5: Enriched, graded data output
To be used and processed in your own systems
The output is an upgraded set of data, including meaning and understanding and can be integrated into your own recruitment platform.