- Sourcing Function and Metrics in Recruitment
- Sourcing Skill Assessment Methodology
- Six Core Areas of Competence
- Assessment and Interview Aid: new eBook “Sourcing Answers” (120 Questions and Solutions)
- Example Questions
- Strengthen Your Skills – Get Educated
- Get Certified
- Assessment, Certification, and Education for Teams
A brand-new “privacy-first” web search engine OneSearch.com from Verizon is out.
Unlike Google, Bing, or Yandex, OneSearch does not have its own index. The search results are Bing-based.
There is no documentation on search operators, but it looks like the operator site: works, and so do a few more, including the Bing-only operator, contains:, which looks for pages with links to files of specific formats. Oddly, as Balazs has pointed out, OneSearch has trouble understanding NOT. I hope we’ll collectively solve that mystery!
The “privacy” aspect can be improved, as some critics say. What is of interest to us though, is that private search engines like OneSearch and DuckDuckGo are not putting users in a “filter bubble.” We can use them to widen our searches.
Web search has a drop-down of the page age restrictions; we can set different time intervals by manipulating the search URL (for example, replace &age=1m with &age=1y). I don’t know if it’s possible to restrict to a language or locality.
OneSearch has a nice set of image search options.
I have found it slightly annoying that OneSearch doesn’t consistently show and highlight keywords in the results. It could be Bing’s quality too; I do not use Bing that often and will need to run some tests. On the positive side, it seems much faster than Bing itself.
Please share your OneSearch observations in the comments or on our
I am happy to announce a new eBook, “Sourcing Answers,” that David Galley and I have just e-published. We had initially conceived the book as an aid to prepare for our Sourcing Certification Exams. However, the book can also serve to help to assess your and your team’s Sourcing skills (whether your goal is to get certified or not) – or perhaps choose questions from the book to use at interviews when hiring Recruiters.
In our industry, assessment of Sourcing skills is vital due to the apparent lack of adequate performance measurements for a Sourcer. Assessments can improve Recruiting performance by identifying Sourcing skill gaps and taking action to fix them. Reviewing solutions and correct answers to the concrete challenges are always educational, as well. This book can serve as an aid in assessments.
By trying to solve the sample questions and comparing your solutions with the ones provided, you will improve your sourcing skills, knowledge, and confidence. The eBook offers “learning by doing” as well as “learning by example.” You would be experiencing optimal approaches to a task, the right way of thinking, and proper tool selections.
The questions in the book are just like those we give at our exams. There is no need for paid subscriptions to any sites. Each question should take you between one and six minutes to answer.
Our test-takers have reported feeling accomplished, having improved their skills and understanding of Sourcing – and having fun taking the exams! We hope you enjoy the questions as well. If you decide that you are ready to get certified, the next Exam week is January 25-31, 2020.
Just like we can’t search for LinkedIn headlines within LinkedIn or by X-Raying, we can’t search for Github Bios – either within Github or by X-Raying. However, we can search for LinkedIn headlines with Custom Search Engines (CSEs). It turns out that we similarly can search for Github Bios with CSEs!
We will be searching using Github X-Ray CSE. I will start off providing sample search strings to look within Bios, then, will give some explanations.
Here you go. “GitHub Bio contains”:
- love python
- clojure OR lisp
- azure devops
- work at Facebook
- CalTech graduate
- Lives in Seattle
- open to new
You can change the arguments, add keywords, and combine with other Google’s and Custom Search Engine operators specific to Github. As you may have noticed, you can use the asterisk * for ANDs and comma , for ORs in the special operators.
You Can Stop Reading Now and Go Enjoy the Searches 🔎🔎🔎
But wait, I also want to tell you that our tool Social List uses CSE operators in the background, and you won’t need to write any operators – just enter your terms and collect results. Here is what a search looks like:
Check it out if you haven’t.
Now, if you are wondering how I came up with the horrible-looking operator more:p:metatags-og_description: (and what is behind the search algorithm in Social List), read on.
CSE – Special Advanced Syntax
Special CSE operators depend on the website and structure of its pages. More specifically, operators depend on what Schema.org, Microformats, and other objects and values are (invisibly) included in the pages’ source code.
The general CSE search operator format is this:
– where data-field-name is an object like Person, data-value is a value, such as “org” (i .e. organization, a Person’s employer), and value is a string like “IBM”– finds pages containing the object Person with a matching “org” value.
Alternative syntax uses just p instead of pagemap:
Google.com doesn’t “understand” the more:… search syntax, but any Google Custom Search Engine does.
Objects and Values to Query
Objects (like Person of schema.org) and values (like employer=”IBM”) are invisibly included in web pages’ source code, in its part called “PageMap”. The big deal is – you can search within objects and their values using CSE operators. PageMap includes data following a variety of standards: Schema.org, Microformats, and others, and also a part called “Metatags”.
In our particular case, a GitHub Bio is stored in Metatags under the tag “og:description” (and is also duplicated under “twitter:description”). I found it by examining the JSON output from a CSE API call:
“twitter:title”: “garris – Overview”,
“twitter:description”: “Works at LinkedIn. Lives in Berkeley. Likes a nice hike. – garris”,
“og:title”: “garris – Overview”,
“og:description”: “Works at LinkedIn. Lives in Berkeley. Likes a nice hike. – garris”,
“dimension1”: “Logged Out”,
One last step and you will catch up with me on the subject. I am going to tell you how I obtained the JSON sample pasted above.
Running CSE API Calls
The APIs query CSEs from software code. It’s also possible to run an API call from your browser address bar.
Using the APIs requires obtaining a KEY (long coded string) from Google, available here. Input for an API call is a KEY, a CSE ID (a value you can copy from the Control Panel), a query string, and (optional) parameters.
You can run an API query from your browser in the following fashion:
– it will look like this:
An API call produces a JSON-formatted output page that you can browse to figure out the operator formats.
While you can examine a page’s structure with various tools (including CSEs themselves), these API JSON outputs provide “the” most accurate information for assembling CSE operators.
Querying structured info on the web is incredibly powerful. It may seem “too technical”, but that is mostly due to odd-looking strings of parameters that create that impression. (But you don’t need to “read” parameters, you just need to copy and paste.) Maybe one day, Google (or someone) will attach a friendly UI to Google CSEs’ structured web search. In the meantime, follow the links to search in Github Bios and definitely try Social List.
Google’s limit of keywords is 32. It’s a challenge for long OR searches, especially for diversity sourcing – for example, searching for women’s first names, Latino last names, or diversity colleges. I am no fan of long ORs on Google (definitely not to list synonyms for a word), but in cases like the above, or searching for target companies or locations, I admit, long ORs would be useful, and 32 is limiting.
I have recently thought of a way to push the number of search terms much further. You can do it via Google Custom Search Engines (CSEs), its Synonyms feature.
Google and CSEs will automatically search for synonyms – it is a “built-in” feature. However, if you want to identify related words that may not quite be considered synonyms, the Synonyms mechanism in CSEs allows that. The limit is 500 terms and 10 synonyms for each term. Synonyms can be defined in a special XML file and uploaded. Keeping synonyms in a file and editing with a simple tool like Notepad++ seems more convenient than editing online.
You can define legitimate synonyms (for example, CV = “curriculum vitae” = resume) to help yourself and your end-users. But nobody will check whether the synonyms you enter are “correct”. You may want to play with the setting, defining words with different meanings as synonyms and see what happens. (Define “top sourcer” as <your name>? Just kidding.)
If you love long OR statements, you can enter up to 500 “synonyms” – some of which can be phrases – for an “artificial” keyword like mysynonyms, in the CSE Synonyms setting, and you will be able to push the limit of keywords from 32 to beyond 500!
When Google started out, it had a database of indexed pages searchable by keywords and advanced search operators such as site:. Gradually, Google began adding semantic search features. (It has been reworking its storage, Index, accordingly, to contain “knowledge” type of data about stored pages). Here are the most significant semantic-oriented additions over the years.
- A while ago, Google started searching for words with the same root (“auto-stemming”).
- About five years ago, we also started seeing keyword synonyms in the results.
- In recent years, Google has started showing featured previews and Knowledge Graph objects, in addition to search results. Pages containing structured information are rewarded by custom snippets (an example would be a page about a movie, shown along with a star rating).
- In 2016, with the introduction of RankBrain, Google started to look at the query context.
- A month ago, with the BERT update, Google has started paying attention to short words that it previously discarded as stop words, to discover query meaning.
- Both RankBrain and BERT are AI-based, so they will work better with time.
- And here is something new and interesting – Google is taking personalized search a step further, having just filed a patent on building user graphs.
Science vs. Art
Google keeps its support for operators, giving us control over search results, and at the same time is greatly expanding semantic features, providing us with the most relevant results. If you use only operator-based search, put your keywords in the quotation marks, or run all searches in the Verbatim mode, you are missing out on powerful semantic search capabilities. Running queries out of a saved spreadsheet or Boolean builder has never worked well but will provide even more limited results than before.
Semantic search functionality is not just for the “simple-minded” user who Googles with a few keywords; it’s applicable to advanced research. The trick for best search experience (how do you like the expression? 😉) is to take advantage of both operator-controlled searches and Google’s interpretation of searches. (It’s not either-or – Google interprets all queries, including those containing operators).
As a metaphor, advanced Googling is like a combination of Science and Art, with the Art part continuing to grow. In practice, Googling needs both the left and right sides of your brain activated. Googling requires knowledge of search operators but also intuition, creativity, curiosity, resourcefulness, and natural intelligence. Everyone has these qualities; it’s a matter of putting them to work.
Looking at multiple examples of creative Googling, reproducing them, and modifying to fit your practice are the fastest ways to up your Google-Fu. You can do so as soon as next week by attending
Sourcing includes three types of search:
- Research – finding info on terminology, target companies, schools, job titles, locations, and industry news
- Search – finding professionals with promising backgrounds
- Cross-referencing – finding additional qualifying professional info and contact info.
“ Research” and “ Cross-referencing” rarely require complex searching. You can accomplish most of the tasks by Googling for a few keywords and using Chrome extensions.
While “ Search” has a technical aspect where you create complex Boolean AND-OR-NOT searches (on LinkedIn or a job board). Advanced Google operators are highly applicable as well. However, you can accomplish quite a bit without any “Boolean complexities”.
Here are some simple – non-technical, “non-Boolean” – approaches to these search tasks. (And there are many more!)
- Have a short question? Google it. While you can’t Google a job description and expect to see anything useful, you can Google for sites where potential candidates might be present, for example:
- Have a lead (a perfect candidate, perhaps someone who had declined an offer, or lives in the wrong place, or is already working in a similar role)? Google his or her name along with the company name or skill keywords. Also, Google the email address in the quotation marks. You will find additional background and may find sites with other professionals “like this one”.
- Search for qualifying phrases someone might have written such as “hired as managing director”. (Sometimes this is mistakenly called “Natural Language Search” – this term means asking your queries in English vs. some computer-oriented notation).
While complex Boolean search must remain part of any sourcing process at this time (please don’t believe that “AI is there” – it is not), you can do around 80% of searches without. Join us at the Sourcing without Boolean webinar to learn all about masterful Googling without using operators and other techniques like the one I described above.
There are two significant recent developments in Google’s algorithm.
 Google’s Operator Numrange is back!
Numrange seems to be working. (Knock on wood!)
 BERT – Search Naturally
The latest Google’s algorithm change, BERT, affects a serious 10% of all queries. Google is now paying attention to “insignificant”, short words, that it had previously ignored as “stop words”. It is noticing words like “at”, “to”, “as”, “if” where they create meaning (try sf to nyc). With BERT, Google’s search is becoming even more semantic and less formal, database-like. (For those wanting “database-like” search experience, Google keeps its Verbatim option).
What BERT tells us is to search natural-language-like, especially if we have a short question. For example, start a query with “what is”, “how many”, “top companies in”, “competitors of”, etc.
BERT (as part of other semantic-oriented changes) teaches us to be friends with working, evolving semantic search systems like Google’s. For better results on Google, search as simple as possible. It’s better to take advantage of machine-learned capabilities vs. suppress search interpretation by using long OR strings or Boolean Builders. Of course, any serious practitioner will use advanced operators, but using ORs is outdated (I mean it).
There are no textbooks on writing useful Google queries. It’s someone’s “natural intelligence” that matters in developing the “search” skill.
Join us for a webinar “Sourcing with Natural Intelligence” on Tuesday, November 12th, where we’ll share the important thinking patterns and multiple concrete examples of this (most) productive Sourcing approach.
As I was finishing the “Hacks” slides for my favorite conference, Sourcing Summit Europe, I stumbled across something I hadn’t seen before. Google Custom Search Engines (CSEs) got a new setting in the control panel:
While selecting Schema.org Objects rely on metadata placed there by web page creators, choosing a KG Object does not. Instead, it reflects Google’s “idea” of which KG Objects are relevant to the page. Therefore, the new option covers a much wider range of sites that can show up in the results. I say this is a true semantic search in a global search engine!
There is a just-announced API for selecting Knowledge Graph Objects, but there is not much explanation from Google how it works. (It could be quite complicated in the back-end, and is undoubtedly updated continuously.) The best way to examine what happens when we use the setting is to create CSEs and see what shows up in the results. (Get your hands dirty and your mind clear 😉).
We can restrict to Schema.org or KG Objects only in Custom Search Engines, but not on Google.com, and it’s time for Sourcers to get to apply the technology. It may sound quite technical, but it’s not; everyone should able to get KG Object searches going. Please come learn all about the new CSE capacity (and everything else about CSEs) at our webinar on October 15th, 2019.
Here are a couple of details on the KG selection, and four examples.
We can select up to five KG Objects, and the search will look for an OR of the five. However, we can search for an AND of two objects with the use of the CSE refinements.
Examples of CSEs that search for:
- Females – example search: java developer san francisco
- Jobs – java developer san francisco
- Curriculum Vitae – java developer san francisco
- OSINT – maltego
Come join us at Become A Custom Search Engines Expert class coming up this week, for an in-depth look at all the options you can set in the CSEs. Seating is limited.
While Google has posted a blog about college search, they did not tell us how to get to that advanced college search dialog, which looks like this for me:
You can search through tons of useful info – Program, Location, Average cost. Tuition, Type, State, Acceptance rate, Size, and Campus setting.
The secret to getting to this dialog is adding this piece – &ibp=htl;splinter – to your search URL. This was my search.
The new capability doesn’t work outside of the US yet (you will see a “not supported” dialog if you are outside of the US) and shows US schools only. But I expect it will be expanded globally. If you want to use the university dialog and are located outside of the US, run one of the IP address changers such as Tunnelbear.
For other Sourcing Hacks, please check the second edition of our eBook!