When I run recruiter training classes, I often ask for the trainees to bring me example positions they are having trouble working on to use for live sourcing training.

During one such class (a little over 2 years ago), I had a recruiter bring me an opening for a challenging position at Google that had been open for a while. He had been working this position for a couple of weeks and had failed to produce a single candidate that Google was interested in interviewing. 

Many Had Already Tried and Failed…

As I asked him for a little background on the position, I found out it had been open for 4 months. 

That’s almost always a bad sign to a recruiter, as it had no doubt been thoroughly beaten up by countless other recruiters/vendors to Google. However, he assured me this was not a “black hole” requirement and that Google would indeed interview and hire candidates.

Now, the position this recruiter was working on was a network performance test engineer, which poses some unique searching challenges because most of the Boolean search strings that recruiters will employ will result in many false positives – resumes of candidates that contain all of the search terms, but who are not primarily responsible for the performance testing of networks. A simple game of “buzzword bingo” would not work for this position.

This was also independently verified by Google, as they commented that most of the candidates they were receiving were not appropriately qualified – most were QA/test engineers who had performance tested software and network applications, but not networks and network hardware specifically.

Give Me Four Hours to Chop Down a Tree…

When I first accepted the challenge of helping this recruiter, my initial searches did pull many false positives. However, after about 20 minutes of manipulating search strings and observing the corresponding changes in the results, I came up with a handful of Boolean queries that resulted in fewer false positives and a larger percentage of resumes of people who were primarily responsible for the performance testing of networks.

Once I gave these searches to the recruiter and he put them to use, in 2 weeks he called to let me know Google had already hired one of his candidates he had found using the Boolean search strings, and he had an interview request for another.

Where Did He Find the Candidates No One Else Could Find?

So where do you think he found these candidates that no one else had been able to find and submit to Google for the network performance testing positions?

Cold calling? Referral recruiting? Blogs? User groups? LinkedIn? Twitter? Facebook?

Nope – he found them on (drumroll please)…………..Monster.

Yes – this recruiter was able to use a resume database that presumably quite a few (if not all) other vendors to Google (and likely Google’s contract recruiters as well) had access to and most likely used to try and find candidates for these positions for several months.

Interestingly enough, the candidates this recruiter was able to find were not new candidates who just posted their resume – their resumes were over 3 months old, which tells me that they had been in Monster’s resume database ever since Google released their network performance testing positions.

I specifically point this out because I love to continuously disprove the commonly held belief that if many recruiters have access to the same resume database that they will be able to find the same candidates, the best candidates, and all of the appropriately qualified candidates.

Holding onto that belief is as foolish as thinking that if 10 people go fishing in the same lake, that they will all catch the same fish, as well as the biggest fish in the lake.

Job Board Resume Databases Do Have High Quality Talent

This is also a good example of how, contrary to popular belief, you actually CAN find extremely good candidates (Google is notoriously elitist, which I respect) on the job boards. I continue to see well-respected recruiting and staffing thought leaders comment on how the job boards have mostly “mediocre” and declining levels of talent.

This may be subjectively true, but certainly not objectively true. Besides, when’s the last time they ran a search and hired someone from a job board? Nothing bothers me more than people talking about something they have little-to-no direct experience with. 

All Boolean Search Strings “Work”

I am 100% positive MANY recuriters searched Monster in an attempt to find candidates for the network performance testing positions at Google. But there’s a funny thing about Talent Mining – you’re only aware of the candidates you actually find, and conversely, you are not aware of the candidates you didn’t find.

However, that does not mean the candidates you want and need aren’t in the database you’re searching. It just means you weren’t capable of finding them. When most recruiters search any particular database, including their own ATS or LinkedIn, and don’t find the people they’re looking for, they assume the candidates don’t exist.

But they’re there. Trust me.

The Power of Talent Mining with Boolean Search Strings

Here’s the search string that produced one of the candidates who was hired at Google:

Test* and (qa or quality) and (perl or tcl*) and (cisco or rout*) and (lab* or case* or plan* or script*) and (ixia or smartbit* or “smart bit”) and (L2* or LACP or STP or RSTP or VRRP or UDLD) and protocol* and (bgp* or eigrp or rip or ospf or mpls)

Interestingly, most of the search terms in the string above were not in the job description or required skills.

So it took me about 20 minutes of experimenting and refining search strings to come up with that search, from which a recruiter was able to make a hire from less than 10 phone calls on a position that had been worked for 4 months by countless other recruiters who had access to the exact same database.

How’s that for ROI?

That’s the power of effective e-talent discovery.

I recently had a reader ask me for help with creating effective Boolean search strings for C programmers. I thought I would share the advice I provided as it can be helpful for sourcers and recruiters who search for tricky skills/technologies, especially common words, single/special characters, and older technologies that many people mention but no longer have current experience with.

Here is the original request:

*****************************************

“I’m having trouble with a particular search string on Monster that I thought you might be able to shed some light on. I’m doing a search for a C Developer (Not C# or C++). This is posing problems, because Monster returns anyone who has the letter ‘c’ in their resume. The search string I am using is:

(”C Developer” or “C programmer” or “C Software Engineer” or “C Engineer” or (”C” and “C”) ) and (”Design” or “develop” or “maintain”) and (”mission critical” or “N-Tier”) and (”Sybase” or “.NET” or “RUP” or “Sun Solaris” or “Rational Unified”) and not (”C#” or “C++”)

(Note: I’ve put and not at the end of that because I found the exact same string with just not returns no results at all, searching all resumes; whereas and not returns results. Not sure why.)

*******************************************************

SEARCH ADVICE

Functional Terms and the Asterisk

I like how the reader has used functional terms such as design or develop, which can enable basic semantic search, but they put those words in quotes, which limits their ability to work as effectively as possible because they force the results to say only those specific words and not variants of them, such as developed, designed, etc.  A more effective use of searching for functional words such as those would be to leverage the fact that Monster supports root word searching via the asterisk. For example: (design* or develop* or maintain*). Using the asterisk in such a manner will produce results of candidates that mention any word variant starting with those root words – which will cover titles (developer) and responsibilities (developed, developing, designed, maintained, maintenance, etc.). Trying to NOT Out C# or C++ 

I noticed that the reader requesting help was trying to NOT out mentions of C++ and C#. On the surface, this seems like an obvious tactic to reduce false positives of C++ and C# developers, however, it can cause significant problems in that it will eliminate every candidate who really does have strong C development experience but simply mentions C++ or C# somewhere on their resume. For that reason alone I’d recommend against it. We don’t want to run the risk of eliminating any relevant results, and there are VERY few software engineers/programmers whose resume mentions C without any mention of other languages anywhere, even if only listed in the skills summary or in educational experience (such as taking a course in C#).

Also, if you noticed from the reader’s comments – they tried running a search by inserting the NOT operator into the search string by itself which did not work.  While this can work on some Internet search engines, none of the major job board resume databases will accept that – you need to say “and not.”

Searching for C

Searching for software engineers who focus on and have current experience with C has ALWAYS been a challenge due to the intrinsic issues of searching for a single character. Most resume databases, ATS’s, and Internet search engines don’t do well when trying to search for single characters.

Additionally, because C is an older language, most companies and departments have over the years left C behind and have migrated to C++, Java, .Net, etc., so finding someone who still predominantly develops applications in C as opposed to any other newer language is very hard. However, there are many companies who still maintain older applications that were originally developed in C that need to be updated or enhanced with new development – so these people DO exist, they’re just not very common.

One of the most annoying things about searching for something like C is that SO many people mention it somewhere in their resume, either during school or in their past work experience, but the majority of their experience is actually in other languages.

Be aware though – there are VERY few people in the world who ONLY mention C in their resume without mentioning C++ or some other language that they’ve had experience with at some point in their career, either on the job or at school. You have to keep in mind that information technology candidates are often told to mention everything they’ve worked with or been exposed to, so don’t be discouraged if you see resumes that talk about C, C++, and Java. You’re going to have to call candidates like that and ASK them what percent of the time they have been responsible for developing applications in each language. You may be surprised by some candidates – you can never judge a candidate by their resume alone.

The question asked was specifically for how to successfully search for C developers on Monster, so let’s get to business. Later in the post I will detail how to search for C programmers in LinkedIn and on the Internet.

Title Search

The idea to target people who identify themselves by specific titles such as “C Developer” is a good one. Titles are horribly limiting, but as a first pass, it’s a good idea because why not target people holding a neon sign over their head saying, “Hello – I’m a C programmer!”?

Beyond Titles

Searching by titles can be a good first pass for any search, but we must always be aware that there are TONS of people who have the experience we need but don’t have a cookie cutter title – and this is especially true of software engineering, as there are so many different titles that people who perform software development can have. Knowing this, we now have to try and find people with C programming experience that do NOT have titles such as “C programmer.”

Going beyond titles, there are a number of things we can try to search for people with solid and recent C experience. Monster and some other databases/search engines CAN be tricked into searching for the single character C if you put quotation marks around it, although in Monster’s case it will still highlight other mentions of C elsewhere throughout the resume, such as the C in C++, and even the C for cell phone number in the contact section. However, it will still highlight C by itself wherever it is.

Even though we’re looking for a C programmer, I’m going to recommend also searching for mentions of C++ as well. This may seem counterintuitive – but when you search for a single character like C and you’re not adding specific titles such as “C Programmer” (which we have already done), you will get TONS of junk results, which is not what we’re looking for.

Just to test my theory, I ran this search:

“C” and not “C++” and (design* or develop* or program* or maintain*) and (rational or RUP or sun or solaris or sybase) 

And I did in fact get tons of garbage – irrelevant results.

So, in order to increase the relevance of the results (getting more software engineers with C programming experience instead of large volumes of non-software engineers and software engineers who develop applications in other languages), we’ll throw in a few combinations of C++ just to test the effect of combining “C” and mentions of C++ as well and see the effect on the relevance of the results:

“C” and (”C and C++” or “C/UNIX” or “C/C++”) and UNIX

Here are a couple of resume snippets. Looking at the results, there are certainly less false positives, and we find more people who are software engineers who mention C and/or C/C++ development. As we can see, the search for C/C++ worked, as did the search for the phrase “C and C++.”  What’s interesting to note is that Monster and most search engines don’t see characters such as the slash (/), yet when we search for “C/C++,” they WILL find C next to C++. So while Monster does not “see” the slash (/), it does “know” something is there, and will return results of C mentioned right next to C++. Same goes for C++/UNIX. In fact, you can use the slash instead of other special characters to effectively search for other difficult-to-search for skillsets (Pro*C, mod_Perl, etc.).

Here we can see that the slash (/) worked for us yet again, pulling mentions of “C, C++.” Monster doesn’t “see” the comma, nor does it even “see” slash, it just knows *something* is there and will pull any mention of the two separated by a small space.

In the case of both resume snippets, there is no way to tell how much time the candidate spent on C development vs. C++ development – anyone who looks remotely close to these results deserves a call to find out more. One of the biggest mistakes sourcers and recruiters make is judging candidates by their resumes and making assumptions.  Let’s take a moment to reflect – these are professional software engineers, not professional resume writers.  I have learned this lesson 1000 times over in my career – give candidates the benefit of the doubt. I have had MANY people hired that I am sure other sourcers and recruiters overlooked just because they made quick assumptions about resumes, not even bothering to take the time to talk with the candidate to find out who they are and what they really have done and can do.

Taking that search one step further, we can add the rest of the search terms that the reader was originally searching for:

“C” and (”C and C++” or “C/UNIX” or “C/C++”) and UNIX and (design* or develop* or program* or maintain*) and (rational or RUP or sun or solaris or sybase)

Looking through the results, we get the usual suspects of false positives, including software engineers who USED to develop applications in C but have been developing in Java for the past 5-10 years, but I am noticing a number of C/C++ developers as well – such as this one:

As with the other results, this person is responsible for developing applications in a number of software languages – they are definitely worth a call to find out how much time they developed applications in C vs, C++ and Java.

Using Monster’s “Most Recent Job Description” Field
Speaking of false positive results of people who mention C in their past but are doing something else now…Monster has a great feature that allows you to enter a single word, phrase, or entire Boolean string in the “most recent job description” field and force all results to specifically mention what we’re searching for in their most recent job description, guaranteeing us that they will make mention of our search terms in their most recent job description, and hopefully actually have current experience with what we need. This is especially hepful when searching for older languages and technologies, enabling us to eliminate results of people who do not mention them in their most recent experience, in an attempt to remove false positives of resumes that mention our keywords once back in 1985, or only in their educational experience.

Searhcing only for the mention of C:

Entering a small Boolean search string:

Employing the NEAR operator

Because Monster is the only job board that supports proximity searching via the Boolean NEAR operator, we can leverage that to attempt to find candidates that specifically talk about developing, designing, or programming in C.

“C” NEAR (design* or develop* or program*) and (”C and C++” or “C/unix” or “C/C++”) and UNIX

In this search, Monster will ONLY return results of resumes that mention C within 10 words of any word beginning with the root of design, develop, or progam, which can be very helpful to target sentences where candidates talk specifically about being responsible for developing, designing, and/or programming applications in C. This is a good example of semantic search, and if you are not familiar with the concept, I highly recommend you read all of the posts under the category of semantic search.

You can see from the above resume snippet the number of times C (or C++) is mentioned within 10 words of any mention of words with the root of design and develop. This is another excellent example snippet, because this candidate talks about C, C/C++, and Visual C++. Definitely worth a call to find out how much time they spent with each programming language – you never know until you pick up the phone.

Searching ALL Resumes

This should go without saying, but I know it doesn’t.  When searching any online job board resume database for anything remotely difficult, be sure to search for ALL resumes. Don’t artificially limit yourself to people who have posted their resumes in the past 30, 60, 90 (etc.) days – search everyone!  By searching ALL candidates, regardless of when they posted their resume, you are exposing yourself to a greater number of candidates, and you are automatically diversifying your candidate pool with both “active” and “passive” candidates. My own research has shown that 75% – 80% of all candidates on each major online job board resume database are over 30 days old.

LINKEDIN

Now that we’ve examined how to search for people with solid C programming experience on Monster, let’s take a look at LinkedIn. While you can always search within LinkedIn using their search interface, I will cover how to leverage the site: command to x-ray into LinkedIn so you are able to see any/all public profiles.

Let’s take a shot at searching only for C without adding any C/C++ to the search and see what Google makes of it.

site:linkedin.com “C” (~design | ~develop) (inurl:pub | inurl:in) -intitle:directory

As we can see, Google goes a little crazy and finds every mention of C, and while some of the results look good, we also get false positive hits of first and middle initials, as well as grades.

Click here for the results

Now let’s shoot for titles and phrases that are specific to C programming and development that do NOT mention C++ anywhere in their profile for a first pass to cherry pick the obvious matches:

site:linkedin.com “C” (”C developer” | “C programming” | “C programmer”) -”C++” (~design | ~develop) (inurl:pub | inurl:in) -intitle:directory

Here we have narrowed the results down to people who specifically mention titles and phrases referencing C development who do not mention C++ anywhere in their profile.

Click here for the results

We know that we are eliminating good results by using -C++ to not return any results of people who do have significant C programming experience but who happen to mention C++ somewhere on their profile. So much as we did on Monster, let’s try adding the C/C++ combos:

site:linkedin.com “C” (”C/C++” | “C/UNIX” | “C and C++”) (~design | ~develop) (inurl:pub | inurl:in) -intitle:directory

Click here for the results

As you can see, we’ve picked up more people to evaluate that talk about C and C++ development. It’s important to realize these results are mutually exclusive from the previous search.

Googling for C Programmers

Last, let’s take a quick look at searching Google for resumes online. First, let’s shoot for C-specific titles and phrases and eliminate C++ from the results:

(intitle:resume | inurl:resume) “C” (”C developer” | “C programming” | “C programmer”) -”C++” (~design | ~develop) -job -jobs

Click here for the results,  which look pretty good.

Now let’s throw some C++ in:

(intitle:resume | inurl:resume) “C” (”C/C++” | “C/UNIX” | “C and C++”) (~design | ~develop) -job -jobs

Click here for the results, which also look good.

CONCLUSION

There are many way to attempt to tackle the intrinsic challenges of searching for single character skills/languages, as well as “outdated” technologies, such as C. Hopefully you’ve learned some tips and tricks along the way. Aside from some core Boolean search best practices, we’ve seen that Monster enables users to leverage searching within the most recent job description to ensure current experience, and Monster also supports the NEAR operator, allowing users to specfically target people who mention developing applications in C.

This post will cover graphic examples of how to achieve semantic search using the NEAR Boolean operator on Monster and on the Internet via Exalead using Accounting and Information Technology hiring profiles.

First, if you have not done so already, be sure to read these 2 posts that throroughly explain the concepts of user-defined semantic search for sourcing and recruiting: Semantic Search for Sourcers and Recruiters, and Semantic Search for Sourcers and Recruiters Round 2. 

Second, if you’re not already familiar with the NEAR operator, I highly recommend you read about it in this post: Extended Boolean – Proximity and Weighting (look for it in the middle of the post under “Fixed Proximity”) before proceeding any further.

The NEAR operator on Monster

Monster is the only major job board resume database that recognizes and supports the NEAR Boolean operator. According to Monster’s documentation, the NEAR operator has a maximum proximity of 10 words. For example, the search string software NEAR programmer returns ONLY those resumes that have software and programmer within 10 words of each other. 

Let’s look at a couple of resume snippets that I used from Monster when I wrote a post on Boolean Search Strings for a Sales Tax Manager. What we’re going to do is go beyond the individual words themselves and look for how the candidates wrote sentences describing specifically what they’ve been responsible for doing. Then we will use the NEAR operator to create Boolean search strings that go beyond simply trying to match the words themselves and attempting to delve into the meaning implied by the words by targeting sentences describing responsibilities.

Notice in both resume snippets, we see verbs like prepared, supervised, managed in close proximity to words like tax, statements, returns, workpapers, schedules, month and quarter end, personnel, staff, etc.

Let’s use the NEAR operator to specifically target sentences where candidates are talking about the types of responsibilites we need them to have had experience with:

prepar* NEAR (tax* or statement* or return*) and (manag* or supervis*) NEAR (personnel or accountants or staff) and tax NEAR (manager or supervisor) and (state or local or federal) and (sales or use)

Breaking down that search – here is exactly what’s going on with the use of the NEAR operators: 

#1 prepar* NEAR (tax* or statement* or return*)

This will require the results to have ANY word starting with the root of tax, statement, or return within 10 words of any word beginning with the root of prepar*

Semantic analysis:
This aspect of the search will be highly likely to return results of resumes that have     sentences mentioning responsibilities such as being responsible for the preparation of tax returns, statements, and returns 

#2 (manag* or supervis*) NEAR (personnel or accountants or staff)

This will require the results to have ANY mention of any word starting with the root of manag or supervis within 10 words of personnel, staff, or accountants

Semantic analysis:
This aspect of the search will be highly likely to return results of resumes that have     sentences mentioning responsibilities such as managing and supervising personnel, staff, or accountants  

#3 tax NEAR (manager or supervisor)

This will require ANY mention of the word tax to be within 10 words of the words manager and/or supervisor

Semantic analysis:
This aspect of the search will be highly likely to return results of resumes that have     titles of tax manager or tax supervisor, as well as resumes with sentences mentioning responsibilities such as managing and supervising tax-related work and/or personnel 

Here are a few examples of the results returned by the above search that clearly demonstrate the NEAR operator hard and effectively at work:

If you’re very observant, you’ll see that the second snippet has a title of “Section Manager – Income Taxes.” The reason I highlight this is that a traditional title search for titles such as “Tax Manager” or “Manager of Tax” could not return that result – a nice example of a candidate that most sourcers and recruiters would not be able to find based on a common title search approach, and proof that hidden talent pools really do exist.

However, using the NEAR operator gives us a handy alternative to specific title searching, and by design, allows us to find candidates with not-as-common titles such as “Section Manager – Income taxes.” Cool.

Now, while the first 50 results of that search had it’s fair share of false positives – such as candidates who are now controllers, CFO’s, and such, but were at some point in their careers responsible for managing tax reporting and personnel, I want to point something out:

Using the NEAR operator, that search pulled 10 direct hits among the first 50 results that had titles of Tax Manager, Supervisor, or Director.

Then, out of curiosity, I took out the NEAR operators and simply replaced them with ANDs:

prepar* and (tax* or statement* or return*) and (manag* or supervis*) and (personnel or accountants or staff) and tax and (manager or supervisor) and (state or local or federal) and (sales or use)

Only 4 out of the first 50 results happened to be direct hits of candidates who had titles of Tax Manager, Supervisor, or Director. So we were able to more than DOUBLE our highly relevant matches among the first 50 results alone by employing the NEAR operator. Sweet.

Now let’s show some love to Information Technology sourcers and recruiters

Let’s say you’re looking for software engineers that, among other things, have deep Java experience as well as specific experience designing portals. This one is easy.

Java and (design* or develop*) and portal* NEAR (design* or develop*)

The double mention of the phrase (design* or develop*) is not redundant.  The first mention is to find any mention of any word starting with the roots design or develop.  The second mention is in conjunction with the NEAR operator, and REQUIRES all results to also have any mention of portal or portals to be within 10 words of any word starting with the root of design or develop.

Semantic analysis:
Using the NEAR operator to ensure that any mention of the words portal or portals is within 10 words of design* or develop* increases the probability that they are mentioned in the same sentence – and if they are mentioned in the same sentence – it’s highly likely that the person is talking about being responsible for designing/developing portals. Which is exactly what we’re looking for.

This is specifically different from just throwing all of the words together and HOPING we get some people who have been responsible for portal design/development. Hope is not a strategy. So we’re using the NEAR operator to target people who ARE responsible for portal design and development, by the design of our Boolean search string.

Here are 3 resume snippets that demonstrate the NEAR operator working its magic:

As you can see, using the NEAR operator worked quite nicely – we targeted the semantics of talking about being responsible for designing/developing portals – and we got it.

The NEAR Operator on Exalead

I realize that not everyone has access to Monster, so let’s take a look at an Internet search engine that everyone DOES have access to – Exalead.

Exalead is the only decent-sized Internet search engine to support proximity searching in the form of the NEAR operator. I say “decent-sized” because it’s not a major search engine in my opinion – mostly because it does not appear to index near as many pages as Google, Yahoo, Live, or Ask, and this is especially and painfully evident when you do back to back searches using the site: command to x-ray into LinkedIn. More on that in another post (here’s a quickie – feel free to run just site:linkedin.com on both Exalead and Google and you will find 10X the total results on Google).

Let’s take a swing at the Java/portal developer search we used above on Monster and point it towards the Internet via Exalead.

(intitle:resume OR inurl:resume) AND java AND (design* OR develop*) NEAR portal* AND NOT job*

Before we look at the results, be aware that unlike Monster, Exalead’s NEAR distance is 16 words – which is getting a little “out there” in terms of proximty.  Also – see how I was able to actually use the asterisk for root word/stemming?  Man that feels good to be able to do that on the Internet. Anyone from Google reading this?

Click here for the results.

Pretty nice results, right? If you check the results, all of them mention portal or portals within 16 words of design*/develop*, in most cases resulting in sentences where the candidate specifically talks about being responsible for/performing portal design/development. Which is exactly what we’re looking for – NOT just people who happen to mention those words somewhere in their resume. We’ve leveraged semantics in our search approach rather than reosrting to the ”buzzword bingo” game.

But wait – there’s more! Exalead also supports configurable proximity. So if 16 words is too far of a gap for you and leads to less relevant results, we can tighen that range.

For example, let’s limit the distance between any mention of design*/develop* and portal* to a maximum of 5 words.

(intitle:resume OR inurl:resume) AND java AND (design* OR develop*) NEAR/5 portal* AND NOT job*

Click here for the results.

We’ve managed to cut the total number of results down significantly, and we’ve also increased the relevance while reducing false positives. Look at how tight those results are! It’s because every single result HAS to mention design*/develop* within 5 words or less of portal*.  We are leveraging semantics heavily here because most mentions of those words in such close proximity are in fact referencing responsibility – we’ve blown past word matching to nail people talking about doing what we need them to have experience with! Am I the only person excited about this?

However, as exciting as this is and as tight as those results are, we have to be cognizant of the fact that there ARE relevant results we just eliminated.  Yup – anyone who mentioned design*/develop* at a range of 6-16 words from portal* was wiped away and we did not see them.  Which is okay, as long as you are aware of this and know how to go back and get them.

As I’ve discussed in many posts, I think the best approach to secondary sourcing is to start tight and highly focused on the most relevant results rather than starting broad and beginning a search buy sifting through tons of false postitives. In other words, if I were target shooting – I would start with a sniper rifle and try to hit the bullseye, rather than start with a shotgun and just be happy to hit the target. 

Applying NEAR to LinkedIn

Let’s use the site: command to use Exalead to x-ray into LinkedIn and exploit Exalead’s configurable proximity search to find Java developers who have been responsible for designing/developing portals.

site:linkedin.com AND java AND (design* OR develop*) NEAR/8 portal* AND (inurl:pub OR inurl:in) -intitle:directory

Click here for the results.

Yup, NEAR works there as well. Every result mentions some mention of design*/develop* within 8 words of portal or portals.  

Also – did you notice how I did not use the -/minus sign coupled with 4 to 6 things I was trying to avoid like jobs, answers, and such? I have found that using (inurl:pub OR inurl:in) is a little cleaner - it simply targets public profiles and all I need to NOT out is intitle:directory in most cases.

Conclusion

Being able to control how close words are mentioned to each other via the NEAR operator enables us to achieve semantic search – tapping into sentence structure and the power of meaning in language. Instead of throwing a bunch of words together and having to sift through large volumes of irrelevant and false positive results, we can attempt to harness semantics to find people based on what they have experience DOING, not just based on what words they happen to include somewhere in their resume.

Kudos to Monster for being the only major online job board to support the NEAR operator, and props to Exalead for not only supporting NEAR, but going a step further and supporting configurable proximity via NEAR/x.

Can’t get enough of semantic search for sourcing and recruiting? My next post will cover how to achieve semantic search for sourcing and recruiting without using any proximity operators. 

Stay tuned!