There are people in the HR/recruiting industry who believe that searching databases, the Internet, and social networking sites to source talent is relatively easy and that it can be automated through the use of technology.
While those people are actually right (to an extent), I am happy to say that unfortunately for them, it’s not that simple.
While anyone can manually write or automate basic searches and find some people, those searches only return a small percentage of the available talent that can be found and they also exclude qualified people. Moreover, there are actually many different levels of searching human capital data in the form of resumes, social media profiles, etc., most of which cannot be replicated or automated by software solutions available today.
In this post, I’m going to share my original slide deck from my SourceCon presentation on the 5 levels of talent mining that I delivered in DC at the Spy Museum (what an awesome venue for a sourcing conference!) and then I’ll dive deep into each distinct level, including examples. Continue reading →
An entertaining blog post by Matt Charney was recently brought to my attention in which he tells the world to shut up and stop talking about Boolean strings – he argues that Boolean search is a dying art and that “investing time or energy into becoming a master at Boolean is a lot like learning the fine art of calligraphy or opening a Delorean dealership.”
You can read the snippet regarding Boolean Strings below – click the image to be taken to the entire post, in which Matt addresses mobile recruiting and employer branding.
I enjoyed Matt’s post and his approach, but I did not find his arguments to be thoroughly sound – although I suspect he wasn’t trying to make them so (after all, his blog is titled “Snark Attack”).
I’m going to take the opportunity to address the points Matt raised – not because I am trying to stay “relevant,” as some might suggest (my blog is a not-for-profit personal passion and I don’t consult/train for a fee), and also not because I have a vested interest in “keeping Boolean search alive” (because I really don’t) – rather, because I am still amazed that a fundamental lack of understanding of search and information retrieval – both “manual” Boolean search and “automated” taxonomy driven and/or AI-powered semantic search – and I am constantly trying to help people not only understand both, but also appreciate their intrinsic limitations, as well as separate reality from hype.
I’m referring to user-defined semantic search, where you tell a search engine exactly what you want with your query, and the search engine doesn’t try to “understand” your search terms or “figure out” what you mean through taxonomies, RDFa, keyword to concept mapping, graph patterns, entity extraction, fuzzy logic, etc.
product managers who work at Microsoft and live in Seattle
software engineers who work at Google and live in New York
(developer OR programmer OR engineer)
underwriters in Charlotte
accountants who live near Alpharetta
I must say that playing around with Graph Search’s natural language query functionality and long list of search options is quite fun. You can easily search for diversity, current titles and employers, years of experience, and of course education.
However, as you can see in the video, my main concern about the limitations of Facebook’s usefulness in sourcing and recruiting is the lack of professional information and the the shallow depth of what is there to be found.
Being able to search for and match people by title and company is useful for some recruiting needs and completely useless for others who need to find professionals with specific experience that cannot be reliably predicted by title alone.
Of course, the allure of the potential of using Facebook for recruiting is largely based on the fact that Facebook has over a billion users globally.
However, Facebook’s challenge in any effort to become a major player in the recruiting solution space is that many people don’t view Facebook as a place to put their professional information so they don’t enter work information on their Facebook profile. Even if they did, they do have the opportunity to hide it from people they don’t know, which is great for them, but bad news for sourcers and recruiters.
What I found especially interesting from my initial test drive of Graph Search is that the number of results for each search was a small fraction of what I know has to actually be available, at least in theory, given the number of Facebook users. For example, Graph Search returned less than 100 people for a search for people who are accountants in the Alpharetta, GA area, while LinkedIn has nearly 6,000. That’s a massive differential!
Do you think that the accountants on Facebook who live in the Alpharetta area just don’t put their work experience on their profile, or that they hide the info from being retrieved by people other than their friends? I’d argue the former at this point. Keep in mind that this issue not only affects search, it also affects advertising. You can’t use Facebook PPC ads to target people who don’t give you critical information to target.
I’ll be posting more videos soon – so stay tuned to see more practical Facebook Graph Search sourcing and recruiting examples.
Oh, and if you didn’t have time to watch the video, no – Facebook’s Graph Search doesn’t currently support Boolean logic.
If you have nearly any tenure in HR, sourcing or recruiting, you’ve probably heard something about “semantic search” and perhaps you would like to learn more.
Well – you’ve found the right article.
As a follow-up to my recent Slideshare on AI sourcing and matching, I am going to provide an overview of semantic search, the claims that semantic search vendors often make, explain how semantic search applications actually work, and expose some practical limitations of semantic search recruiting solutions.
Additionally, I will classify the 5 basic levels of semantic search and give you examples of how you can conduct Level 3 Semantic Search (Grammatical/Natural) with Monster, Bing, and any search engine that allows for fixed or configurable proximity.
Most sourcing, recruiting, and staffing professionals are familiar with the basic Boolean operators of AND, OR, and NOT. However, I have found that few are familiar with what some refer to as “extended” Boolean functionality, such as proximity search and term weighting.
Proximity and term weighting, where supported, are not actually logical (Boolean) operators – they are more accurately referred to as text or content operators.
Whatever you call them – extended Boolean or text operators – they offer sourcers and recruiters significantly more control, power and precision when executing searches, and in the hands of an expert, they can enable semantic search. Continue reading →