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How
do you find a needle in a haystack? These
days, it seems every job opening yields
a flood of resumes. And your database has
grown to hold tens or hundreds of resumes.
But so many resumes aren't right for the
job and conventional search and screening
tools are confounded by scale. If a search
is defined on the basis of keywords, a simple
query might yield an unmanageable number
of results. Burning Glass turns this problem
on its head by providing the technology
to unlock the potential of scale. Because
it is built on an advanced artificial intelligence
engine, the more candidates contained within
the database, the more likely Burning Glass
solutions are to find a strong match.
With
LensMatch™, you no longer need to waste
all that time and money reviewing resumes
that don't fit. LensMatch™ deploys its leading-edge,
artificial intelligence-based Predictive
Matching™ engine to measure how suitable
each candidate is for the position. And
it does it all automatically so you can
focus your resources on the viable candidates
and avoid those who are unqualified. In
side-by-side field tests, LensMatch™ picks
out the very same applications selected
by experienced recruiters.
And
our JobMatch™ technology deploys the same
engine in reverse, enabling candidates to
skip irrelevant listings and jump straight
to the jobs that fit their skills and experience.
LensMatch™
LensMatch™
provides the most powerful searching, screening,
and matching tools in the industry. LensMatch™
reads and understands both resumes and job
descriptions so that it can focus recruiters
on the most relevant candidates for a job,
based not only on specific skills and experiences
but also on career profiles. Given a collection
of candidates described by text resumes
or suitable profiles (such as those created
through online forms), LensMatch™ rapidly
searches for those candidates best suited
to a specific position and returns a list
ranked by probability of placement. It can
also seek out the most relevant jobs for
a candidate and can find more resumes similar
to that of an "ideal" candidate.
Other
solutions provide search for matching documents
simply on the basis of words or correlated
words (what they refer to as concepts).
LensMatch™ keeps results relevant by reading
resumes the same way real people do - as
a holistic set of skills and experiences,
not just as a bag of keywords. By understanding
each candidate's strengths, it is able to
measure how suitable each candidate is for
the position. As a result, LensMatch™ can
sort through millions of resumes at a time
to identify the candidates your clients
are most likely to hire.
LensMatch™
offers four ways to find the most viable
resumes for the job.
-
Smartlist™.
LensMatch™ uses neural-network predictive
technologies to shortlist the candidates
most compatible with a job description
- based on a full evaluation of skills,
experiences, and career path.
-
Contextual
Searching. Much more than just keyword
searching, LensMatch™ enhances relevance
by examining search-term context. For
example, limit a search to only candidates
who have used a certain skill in the
past year or who live within 20 miles
or search for a term within a specific
section of the resume.
-
Resume
Cloning™. Sometimes you come across
a model candidate. LensMatch™ lets you
"clone" the candidate to find others
with similar attributes.
-
Skills
Identification. LensMatch™ allows
users to search for skills - even those
that the candidate may not have included
in the resume.
JobMatch™
You
can also deploy the Burning Glass matching
engine to help candidates search through
the job postings on your site or to notify
passive job seekers when a particularly
relevant opportunity arises. Based on the
candidate's skills and experiences, JobMatch™
will search rapidly through millions of
postings to find the ones that look most
appropriate. Using JobMatch™, candidates
can simply upload a resume on your site
and immediately see relevant vacancies -
all without having to complete a form. Or
run JobMatch™ on a batch basis to generate
nightly or weekly email notifications.
The
advantages are significant. Relevance builds
trust. As candidates see matches that fit,
they pay more attention and rely more strongly
on your site for job opportunities. What's
more, because JobMatch™ directs candidates
to the most appropriate opportunities for
them, you will see applicant quality improve
as candidates self-select into positions
that match their background.
What
is Predictive Matching™ technology?
Burning
Glass's Predictive Matching™ technology
is based on mathematical models of employer
and candidate behavior, determines the degree
of compatibility between the candidate and
the job posting. The models seek out contextual
correlations, both within a document and
across documents, in order to identify conceptual
similarity - not just matching of keywords.
Burning
Glass deploys the only tools on the market
capable of evaluating an application's relevance
holistically. We not only verify sufficiency
of match between the resume and job description
but also evaluate the statistical probability
that this job could be the next step on
the candidate's career path. Based on millions
of hiring transactions, the KnowledgeMine™
characterizes entities - individual employers,
educational institutions, job titles, skills,
degrees - and the long-term impact they
have on careers. Our technology has instilled
the complex behavior patterns in these resumes,
and uses those patterns to build predictive
models for employment.
How
does Burning Glass apply Predictive Matching™
to resume search?
Burning
Glass's Predictive Matching™ technology
extracts detailed information from resumes
and job posting such as applicant skills,
educational institutions, degrees, majors,
job titles, industries, companies, etc.
within the context in which they appear.
As users enter their search criteria, it
automatically infers related skills and
alternative wordings. The information is
then used to devise numerous variables to
match resumes with job postings and then
weighted appropriately by a neural network
model. The final result is a score that
represents the mathematical probability
of a match between the resume and the job
posting.
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