APPLICATION

How Does Parsing Work?

Most searching and matching engines are designed around the concept of matching keywords (a “Boolean” search) rather than profiles, but this First Generation search technology is not effective at finding candidates.

Another search technology is a statistical inference engine. These engines analyze collections of documents and look for clusters of words that often appear together. These engines are sometimes called “conceptual search” engines. Conceptual search technology is Second Generation.

The Third Generation of search technology is semantic matching. Semantic Matching Engines (SME) extract terms from text and determine their meaning and values.

The SME used by the dotStaff™ Vendor Management System is the Fourth Generation of matching technology. Our parsing engine not only extracts semantic data, it also extracts and uses metadata. For example, a semantic matching engine may extract the term “Java” and determine that it is a skill. The SME will extract a skill called “Java” and determine that it has a cumulative value of 45 months, and a date of last use of June, 2007. It will further know that the skill called Java was found within the context of a profile that has (or requires) 12 years of total experience (metadata).

Thus, the SME is a true profile matching engine. The SME can parse/extract/classify/characterize and construct profiles of candidates and jobs and match profiles in any direction (jobs => jobs, jobs => candidates, candidates => jobs, candidates => candidates).

 

For example:

Iif you are looking for a “mid-level Java programmer,” the SME finds resumes of candidates with 4 to 8 years of Java programming, who are currently using Java. In other words, it finds people who are exactly what you are looking for - mid level Java programmers.

How?

The dotStaff™ SME finds a keyword and it evaluates all of the relevant criteria to determine if the keyword is a correct match or a false positive. [A false positive is an apparent match, which on human examination is found to be a false match because the meaning was different than what the searcher intended.]  When the SME identifies a keyword match, the SME investigates the context, values and meaning of the keyword to evaluate whether the keyword is an actual match or just a false positive.

	Specifically, the SME examines:
		The context of the match.
		The meaning of the match.
		The value of the match.
		The experience profile of the match.
		The skills profile of the match.
		The ranged data values of the match.

 

The simplistic keyword search engine will “match” all candidates with the word “Java” on their resumes.  This is really not a search; it’s actually what we refer to as a dredge. 

Thus, when using the dotStaff™ VMS, the search is precisely targeted.  The SME reveals the candidates whose profiles exactly match the job order profile with no false positives, in just a few seconds.

 

Want to learn more?  Please contact us at sales@dotStaff.com or complete a dotStaff™ demo request.