Data Enrichment APIs

Textkernel’s taxonomies comprise a comprehensive inventory of professions and skills found in job postings and resumes. The professions (over four thousand) and skills (over eleven thousand) are organized hierarchically, and each of them is linked to a number of synonyms, acronyms, and other ways of wording.

How does the standardization of profession and skill data contribute to matching people and jobs? Let’s look at an example:

On the left we see a situation where matching happens merely on the basis of textual overlap. Because the words do not match exactly, perfectly suitable candidates would be overlooked. If taxonomy-based standardization is added to the process, as on the right, the job titles and skills mentioned in the documents are recognized as identical. Thus, data enrichment helps unlock the potential of your talent data.

Connecting roles to roles

In addition to matching specific profiles and job listings, the Ontology API makes it possible to understand how roles relate to each other in terms of the skills they require. Given a current and subsequent role, it indicates which skills are “transferable”, and which are likely to require upskilling activities.

Reliable analytics also requires standardization of data. To illustrate this, let’s look at a scenario with and without standardization of job titles.

In the scenario on the left, we’re essentially counting words, not jobs. Without accounting for synonyms and variation in wording’, the results of analyses like these are not actionable. The Professions API and Skills API help achieve this: they represent your data in a way that goes beyond words: in terms of the units (professions, skills) that are actually of interest.