With the rapid advances of technology and the advent of Web 2.0 penetration into the fabric of every vertical known to mankind, it’s rather ironic that the Recruiting vertical hasn’t embraced Web Semantics as much for enhancing the overall productivity of the Recruiter. 

The traditional search parameters as we all know pulls us towards using key words to search databases (structured) and are in most instances one dimensional in their approach towards database queries.  Syntactic searching only yields results limited to Key words and thus limits “search” in general. 

Semantics when applied to Recruiting in particular can yield the much needed additional sets of eyes for a given search.  With the advent of vertical search engines/job aggregators and the ubiquitous nature of general search engines there doesn’t seem to be any dearth of data, however information needs to be interpreted from these data sets.  We are also using multiple sources of data from various formats like databases, spreadsheets, RSS feeds, etc to feed our hunger for sourcing talent.  The secret lies in quickly and meaningfully exploring these humongous data sets for the advantages of the average recruiter.

Employers in particular and Recruiters in general are constantly seeking newer ways to automate the pre-screening of candidates. Unfortunately the traditional job boards, portals are not helping the cause.  Please don’t tell me quantity can win over quality.  It’s not how many licenses I have on a given board that will help an Employer, or a Recruiting company to better their results, rather the effective usage of key technology traits like Semantics that could differentiate them.  How? I am glad you asked.

Pre-defined Vocabularies for crafting job specs:

Traditional job postings are written in free text and we all know it limits machine processability.  Instead by using pre-defined vocabularies for defining the “spec” will yield better results.

Annotated job postings for better visibility and integration:

By using Semantic Web technologies the job postings can be better integrated and have increased visibility truly leveraging the distributed architecture principles of the web.  Instead of having a job posted on your career site and paying a Job board/portal for the same job to be posted on their web site this approach could help in better manageability of the jobs and budgets associated with the same.

Candidate Screening:

Let’s face it we all have been guilty of not being able to unearth a hidden gem from our internal databases, job boards, and or the deep web since we are limited by our ability to search.  Albeit Boolean operators help us quite a bit in mining data sets, semantics can unearth a whole lot of relevancy from unstructured data formats as well.  Let’s say you are searching for a “Project Manager”, and your system queries produce 50 resumes of “Project Managers” using machine and algorithmic syntax as the key differentiator.  However the system queries in the traditional sense will not be able to yield results from resumes where the candidate mentions about “project managing”, “Managing a project”, “Used Primavera for projects”, “Extensive knowledge of Pert and Gantt” etc.  We can increase the efficiency of ‘search” and help us (the recruiters) better our screening by incorporating similar technologies.