Artificial Intelligence Matching

100+ Free Sourcing & Recruiting Tools, Guides, and Resources

Posted by | Analytics, Artificial Intelligence Matching, Best Practices, Big Data, Bing, Boolean, Boolean Search Experiments, Boolean Search Tips and Tricks, Data Science, Diversity Sourcing, Email Verification, Extended Boolean, Facebook, Future of Sourcing and Recruiting, Google, Google Plus, Graph Search, Hidden Talent Pools, How-To's, Human Capital Data, Information Retrieval, Lean/JIT Recruiting, LinkedIn, LinkedIn Search, LinkedIn SEO, Moneyball Recruiting, Monster, Monster vs. Google, Myths and Misconceptions, Passive Sourcing and Recruiting, Predictive Analytics, Proximity Searching, Recruiting Technology, Referral Recruiting, Resume Aggregators, Resume Sourcing, Resume Sourcing vs. Cold Calling, Search Automation, Search Process, Semantic Search, Social Discovery, Social Media, Social Networking, Social Recruiting, Sourcing, Sourcing and Recruiting, Sourcing Automation, Sourcing Challenges, Sourcing Mistakes, Talent Communities, Talent Mining, Talent Warehouse, Training Sourcers and Recruiters, Twitter, x-ray search | 3 Comments

 

It’s been a LONG time coming, but I finally got around to updating my free sourcing & recruiting tools, guides and resources page where I now keep a current list of the best of my work all in one place for easy bookmarking and reference.

You can find it here on my main page:

 

Here is where you can find all of the best of my Boolean Black belt content all in one place - free sourcing and recruiting how-to guides, tools, presentations, and videos - be sure to bookmark it, and if you're feeling  friendly, tweet it, share it on LinkedIn and/or +1 it on Google Plus.  Many thanks!

 

Additionally, I thought I might as well put all of my best work all in one blog post as well – over 110 of my articles in one place for easy referencing!

My blog is a pursuit of passion and not of profit – if you’ve ever found anything I’ve written helpful to you, all I ask is that you tweet this out, share it on LinkedIn, like it on Facebook, or give this a +1 on Google.

Many thanks for your readership and support – please pay it forward to someone who can benefit.

Big Data, Analytics and Moneyball Recruiting

Big Data, Data Science and Moneyball Recruiting

The Moneyball Recruiting Opportunity: Analytics and Big Data

Human Capital Data is Sexy – and Sourcing is the Sexiest job in HR/Recruiting! 

Is Sourcing Dead? No! Here’s the Future of Sourcing

The End of Sourcing 1.0 and the Evolution of Sourcing 2.0

How to Find Email Addresses

How to Use Gmail and Rapportive to Find Almost Anyone’s Email Address

Social Discovery

2 Very Cool and Free Social Discovery Tools: Falcon and TalentBin

Talent Communities

The Often Overlooked Problem with Talent Communities

Lean / Just-In-Time Recruiting / Talent Pipelines

What is Lean, Just-In-Time Recruiting?

Lean Recruiting & Just-In-Time Talent Acquisition Part 1

Lean Recruiting & Just-In-Time Talent Acquisition Part 2

Lean Recruiting & Just-In-Time Talent Acquisition Part 3

Lean Recruiting & Just-In-Time Talent Acquisition Part 4

The Passive Candidate Pipeline Problem

Semantic Search

What is Semantic Search and How Can it Be Used for Sourcing and Recruiting?

Sourcing and Search: Man vs. Machine/Artificial Intelligence – My SourceCon Keynote

Why Sourcers Won’t Be Replaced By Watson/Machine Learning Algorithms Any Time Soon

Diversity Sourcing

How to Perform Diversity Sourcing on LinkedIn – Including Specific Boolean Search Strings

How to Use Facebook’s Graph Search for Diversity Sourcing

Social Recruiting

How to Find People to Recruit on Twitter using Followerwonk & Google + Bing X-Ray Search

Google Plus Search Guide: How to Search and Find People on Google Plus

Facebook’s Graph Search Makes it Ridiculously Easy to Find Anyone

How to Effectively Source Talent on Social Networks – It Requires Non-Standard Search Terms!

How a Recruiter Made 3 Hires on Twitter in Six Weeks!

Twitter 101 for Sourcers and Recruiters

Anti-Social Recruiting

How Social Recruiting has NOT Changed Recruiting

Social Recruiting – Beyond the Hype

What Social Recruiting is NOT

Sourcing Social Media Requires Outside the Box Thinking

Social Networking Sites vs. Job Boards

LinkedIn Sourcing and Recruiting

Sourcing and Searching LinkedIn: Beyond the Basics – SourceCon Dallas 2012

LinkedIn’s Dark Matter – Profiles You Cannot Find

How to Get a Higher LinkedIn InMail Response Rate

The Most Effective Way to X-Ray Search LinkedIn

LinkedIn Catfish: Fake Profiles, Real People, or Just Fake Photos?

LinkedIn Search: Drive it Like you Stole It – 8 Minute Video of My LinkedIn Presentation in Toronto

How to Search LinkedIn and Control Years of Experience

How to Quickly and Effectively Grow Your LinkedIn Network

How to View the Full Profiles of our 3rd Degree Connections on LinkedIn for Free

How to Find and Identify Active Job Seekers on LinkedIn

LinkedIn Profile Search Engine Optimization

Free LinkedIn Profile Optimization and Job Seeker Advice

Do Recruiters Ruin LinkedIn?

The 50 Largest LinkedIn Groups

How to See Full Names of 3rd Degree LinkedIn Connections for Free

How I Search LinkedIn to Find People

LinkedIn’s Undocumented Search Operator

Does LinkedIn Offer Recruiters any Competitive Advantage?

Have You Analyzed the Value of Your LinkedIn Network?

Where Do YOU Rank In LinkedIn Search Results?

What is the Total Number of LinkedIn Members?

Beware When Searching LinkedIn By Company Name

LinkedIn Sourcing Challenge

How to Search for Top Students and GPA’s on LinkedIn

What’s the Best Way to Search LinkedIn for People in Specific Industries?

18 LinkedIn Apps, Tools and Resources

LinkedIn Search: What it Could be and Should be

How to Search Across Multiple Countries on LinkedIn

Private and Out of Network Search Results on LinkedIn

How to “Unlock” and view “Private” LinkedIn Profiles

Searching LinkedIn for Free – The Differences Between Internal and X-Ray Searching

Sourcing and Boolean Search

Basic Boolean Search Operators and Query Modifiers Explained

How to Find Resumes On the Internet with Google

Challenging Google Resume Search Assumptions

Don’t be a Sourcing Snob

The Top 15 Talent Sourcing Mistakes

Why Boolean Search is Such a Big Deal in Recruiting

How to Become a World Class Sourcer

Enough with the Exotic Sourcing Already – What’s Practical and What Works

Sourcing is So Much More than Tips, Tricks, Hacks, and Google

How to Find, Hire, Train, and Build a Sourcing Team – SourceCon 2013

How to Use Excel to Automatically Build Boolean Search Strings

The Current and Future State of Sourcing

Why So Many People Stink at Searching

Is your ATS a Black Hole or a Diamond Mine?

How to Find Bilingual Professionals with Boolean Search Strings

How to Best Use Resume Search Aggregators

How to Convert Quotation Marks in Microsoft Word for Boolean Search

Boolean Search, Referral Recruiting and Source of Hire

The Critical Factors Behind Sourcing ROI

What is a “Boolean Black Belt?”

Beyond Basic Boolean Search: Proximity and Weighting

Why Sourcing is Superior to Posting Jobs for Talent

The Future of Sourcing and Talent Identification

Sourcing is an Investigative and Iterative Process

Beyond Boolean Search: Human Capital Information Retrieval

Do you Speak Boolean?

Is Recruiting Top Talent Really Your Company’s Top Priority?

Sourcing is NOT an Entry Level Function

Boolean Search Beyond Google

The Internet Has Free Resumes. So What?

How to Search Spoke, Zoominfo and Jigsaw for Free

Job Boards vs. Social Networking Sites

What to Do if Google Thinks You’re Not Human: the Captcha

What if you only had One Source to Find Candidates?

Passive Recruiting is a Myth – It Doesn’t Exist

Sourcing: Separate Role or Integrated Function?

The #1 Mistake in Corporate Recruiting

How I Learned What I Know About Sourcing

Resumes Are Like Wine – They Get Better with Age!

Why Do So Many ATS Vendors Offer Such Poor Search Functionality?

Do Candidates Really Want a Relationship with their recruiter?

Recruiting: Art or Science?

What to Consider When Creating or Selecting Effective Sourcing Training – SourceCon NYC

The Sourcer’s Fallacy

Sourcing Challenge – Monster vs. Google – Round 1

Sourcing Challenge – Monster vs. Google – Round 2

Do You Have the Proper Perspective in Recruiting?

Are You a Clueless Recruiter?

Job Boards and Candidate Quality – Challenging Popular Assumptions

When it Comes to Sourcing – All Sources Are Not Created Equal

Boolean Search String Experiments

Boolean Search String Experiment #1

Boolean Search String Experiment #1 Follow Up

Boolean Search String Experiment #2

 

The End of Sourcing 1.0 is Near, Sourcing 2.0 Just Beginning

Posted by | Artificial Intelligence Matching, Big Data, Future of Sourcing and Recruiting, Job Posting, Sourcing, Sourcing Automation | 20 Comments

 

In case you haven’t read Dr. John Sullivan’s recent article entitled, “The end of sourcing is near…the remaining recruiting challenge is selling“, I highly recommend that you do so.

While I agree with some of the points that Dr. Sullivan raises, I disagree with others as I believe he has an oversimplified view of sourcing.

I argue that some basic and common sourcing functions and tactics will be coming to an end soon, and in fact, they have already ended in companies that are on the leading edge of sourcing.

However, as with many corporate functions, there will never be an end to sourcing itself – there will only be an evolution.

What follows is my sourcing manifesto.

Read further to explore:

  • Why sourcing exists in the first place
  • The underlying flaws of the “everyone is easy to find” argument
  • The limits of matching technology
  • Why big data requires people to make sense of it
  • My definition of sourcing
  • Strategic vs. tactical sourcing
  • The true value of sourcing
  • What can (and should!) be automated in sourcing
  • Sourcing 1.0 vs. 2.0

You should be advised that this is a lengthy article – if you’re looking for a quick read, you won’t find it here. Read More

Talent Sourcing: Man vs. AI/Black Box Semantic Search

Posted by | Artificial Intelligence Matching, Boolean Logic, Dark Matter, Extended Boolean, Future of Sourcing and Recruiting, HCDIR, Human Capital Data, Information Retrieval, Recruiting Technology, Resume Sourcing, Search Automation, Semantic Search, Sourcing, Sourcing Automation | 2 Comments

Back in March 2010, I had the distinct honor of delivering the keynote presentation at SourceCon on the topic of resume search and match solutions claiming to use artificial intelligence in comparison with people using their natural intelligence for talent discovery and identification.

Now that nearly 2 years has passed, and given that in that time I’ve had even more hands-on experience with a number of the top AI/semantic search applications available (I won’t be naming names, sorry), I decided it was time to revisit the topic which I am very passionate about.

If you’ve ever been curious about semantic search applications that “do the work for you” when it comes to finding potential candidates, you’re in the right place, because I’ve updated the slide deck and published it to Slideshare. Here’s what you’ll find in the 86 slide presentation:

  • A deep dive into the deceptively simple challenge of sourcing talent via human capital data (resumes, social network profiles, etc.)
  • How resume and LinkedIn profile sourcing and matching solutions claiming to use artificial intelligence, semantic search, and NLP actually work and achieve their claims
  • The pros, cons, and limitations of automated/black box matching solutions
  • An insightful (and funny!) video of Dr. Michio Kaku and his thoughts on the limitations of artificial intelligence
  • Examples of what sourcers and recruiters can do that even the most advanced automated search and match algorithms can’t do
  • The concept of Human Capital Data Information Retrieval and Analysis (HCDIR & A)
  • Boolean and extended Boolean
  • Semantic search
  • Dynamic inference
  • Dark Matter resumes and social network profiles
  • What I believe to be the ideal resume search and matching solution
Enjoy, and let me know your thoughts.

Why So Many People Stink at Searching

Posted by | Artificial Intelligence Matching, Human Capital Data, Information Retrieval, Iterative Search, Search Process, Semantic Search | 5 Comments

The trouble with search today is that people put too much trust in search engines – online, resume, social, or otherwise.

I can certainly understand and appreciate why people and companies would want to try and create search engines and solutions that “do the work for you,” but unfortunately the “work” being referenced here is thinking.

I read an article by Clive Thompson in Wired magazine the other day titled, “Why Johnny Can’t Search,” and the author opens up with the common assumption that young people tend to be tech-savvy.

Interestingly, although Generation Z is also known as the “Internet Generation” and is comprised of “digital natives,” they apparently aren’t very good at online search.

The article cites a few studies, including one in which a group of college students were asked to use Google to look up the answers to a handful of questions. The researchers found that the students tended to rely on the top results.

Then the researchers changed the order of the results for some of the students in the experiment.  More often than not, they still went with the (falsely) top-ranked pages.

The professor who ran the experiment concluded that “students aren’t assessing information sources on their own merit—they’re putting too much trust in the machine.”

I believe that the vast majority of people put too much trust in the machine – whether it be Google, LinkedIn, Monster, or their ATS.

Trusting top search results certainly isn’t limited to Gen Z – I believe it is a much more widespread issue, which is only exacerbated by “intelligent” search engines and applications using semantic search and NLP that lull searchers into the false sense of security that the search engine “knows” what they’re looking for. Read More

Sourcers and Recruiters – Don’t Fear Watson or Semantic Search

Posted by | Artificial Intelligence Matching, Semantic Search, Talent Intelligence | 12 Comments

I’ve read a few articles recently talking about IBM’s Watson and how the technology they developed may be the harbinger of unemployment for people in many professions.

Here’s one from Fortune magazine, asking if IBM’s Watson will put your job in jeopardy.

Here’s another suggesting that those who train others in Internet, social media, ATS, and resume database sourcing techniques and strategies will be eventually eliminated by semantic search solutions.

Watson Winning at Jeopardy isn’t Surprising

First, let’s first recognize that it’s an apples to oranges comparison between Jeopardy and sourcing/recruiting. Read More