SeeMore service unites semantic search with the cloud

Based on 6Sense search technology, SeeMore provides tools to intelligently search many employee data sources from one place

Recruiters and hiring managers are facing an embarrassment of riches as they look to match viable job candidates with open positions. The trick has been figuring out how to quickly and accurately search through troves of disparate resume databases -- both external and internal -- to pinpoint which prospective candidates truly have the desired skills and education.

To aid in the struggle of extracting wheat from all that chaff, today unveiled a service called SeeMore that leverages Monster's 6Sense semantic search and the cloud to help recruiters intelligently scour through an array of resume data sources -- such as job boards, social networks, and ATSes (application tracking systems) -- from a single pane. The service is designed to complement organizations' existing HRISes (human resources information systems) and TMSes (talent management systems).

Basically, the service enables a hiring manager or recruiter to point the service to any number of resume databases -- no importing or exporting of data is necessary -- and search them all as though they were a single pool of data. That's pretty handy in and of itself.

But has injected semantic smarts into the 6Sense search, intended to make searches easier and more fruitful. For example, a user could enter the search term "vp finance." Rather than simply spewing out all names of candidates with resumes containing one or both of those specific terms, it would present a list of prospective candidates with job experience similar to that you would expect of a vice president of finance, whether or not they ever held that specific title. That functionality means that, say, potentially qualified directors of finance would show up in search results; unqualified vice presidents of sales at a financial services company would not.

Another example: Under the education field, a user could enter "top business school," and the top results would include candidates who attended business schools at Harvard, Stanford, and MIT; candidates who studied at Hollywood Upstairs Business School wouldn't get high billing.

While filling out the search fields, the user has the option of choosing whether particular skills, education levels, and the like are required or simply "nice to have." It then uses those specifications along with the search terms to present a list of candidates, each of which is assigned a score between 1 and 10; the higher the score, the better fit with the candidate.

The resulting searches yield details from each candidates resume; specific skills, job titles, and company names are highlighted in bright yellow to indicate why a given candidate made the cut.

From there, a user can select several candidates and compare the contents of their respective resumes side-by-side to easily compare education, skills, salary requirements, and so forth.

The service also provides a recruiter with the ability to create reports on the fly. For example, one could search for all candidates in the resume pool that currently work as mobile-app developers at select rival companies. One could also view the desired salary range among, say, network administrators with Cisco certification living in the Midwest. The possibilities stretch on.

SeeMore, currently in beta, will now be available to customers in the United States and the United Kingdom. is not disclosing pricing details, only that it varies based on the number of resumes hosted and, to a smaller extent, the number of users a customer wants on the system.

This article, " SeeMore service unites semantic search with the cloud," was originally published at Get the first word on what the important tech news really means with the InfoWorld Tech Watch blog. For the latest business technology news, follow on Twitter.