Tag Archives: Search Relevance

Using Extended Boolean to Achieve Semantic Search in Sourcing

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When it comes to sourcing and recruiting, semantic search is perhaps the most powerful way to quickly find people who have experience you’re looking for.

Now, I am not talking about black box semantic search (e.g., Google, Monster’s 6Sense, etc.).

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.

If you’re not very familiar with semantic search (for sourcing – not search engines), I strongly suggest you read my comprehensive article from January 2012 on the subject: The Guide to Semantic Search for Sourcing and Recruiting. Continue reading →

Why So Many People Stink at Searching

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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. Continue reading →

LinkedIn Search Results Sorting: Relevance or Keyword?

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Find_People_on_LinkedIn from www.linkedin.comWhen I deliver presentations on how to leverage LinkedIn to source candidates, I have the opportunity to get a sense of what most people seem to know about using LinkedIn.  Recently I have been making it a point to ask how people tend to sort their search results when searching LinkedIn, and the overwhelming majority leave their results sorting at the default value, which is “relevance.”

LI_Search_Sort6

I find this especially interesting, because most people do not seem to realize that when you sort your search results by “relevance” on LinkedIn, you are not getting results based solely on the search terms entered – you are getting results ordered by a combination of factors – including your “social graph.” 

LinkedIn’s definition of “relevance” is decidedly different than practically every other searchable source of potential candidates – Monster, Google, Applicant Tracking Systems, Twitter, etc. – and what LinkedIn *thinks* is relevant to you may actually not be based on what you are specifically looking for. Continue reading →