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The recruitment industry invests a lot of time and effort into the parsing and pulling of data from resumes and job descriptions. Once it has been extracted, resume data is matched with job descriptions to filter candidates. The whole process is quite tedious and gives rise to an urgent need for the standardization of data

The form and structures of skills data, has huge implications in the recruitment function. Resumes and Job Descriptions are two key documents that are used in recruitment technology. Both are usually very text heavy. This text, though easy enough to process, poses inherent challenges when it comes matching people to jobs. This might also impact

We have created an entirely new language for skills and then gone on to build multiple ways to align it effectively to existing HR processes. Many of you might be curious about how this really functions. In this article we will give you a quick lowdown on how the IYS Skills Ontology can be used

Skills data is typically over-complicated – in the form of resumes and job descriptions – or oversimplified – in the form of skills selection interfaces that are too basic. Resumes and job descriptions are text based and carry too much information for today’s world of skimming through content. At the other end of the spectrum,

Standards exist across almost every field – communication protocols, engineering, healthcare…the list goes on. Standards help in moving information from one pool of information to another and in creating a platform for rich analytics. In the case of healthcare, for instance, standardization supports a common understanding between doctors, insurers and others. Standardization of Data on

Maps enable us to know where we are, places near and far, how to get there et al. They make the world exciting to experience. Being an HR professional, I wondered why not a map of skills that can similarly help everyone become aware of their skills, appreciate them and perhaps explore new ones? At

Big Data, as I see it, is understanding one’s preferences in finer detail and then increasing the probability of the choices that fit our preferences to be presented to us. So, there are two things in play – First is profiling and the second is selection. Let me explain. I like reading books and a

Hiring managers today complain about not able to find candidates with the right skills for the job, but are they looking for the right skills? A candidate who has good visualizing and UX skills and has worked on CSS3 may be rejected just because they “know” but have not worked on JQuery is ridiculous! It