LinkedIn and the Galene Search Update

Last week, LinkedIn announced a new search architecture which they are calling Galene. Siram Sankar, Principal Staff Engineer at LinkedIn, authored a very detailed blog post explaining the need for Galene, what it is currently doing, and what they plan for Galene to be able to do in the future.

Below are a couple bullets covering the basics of the upgrade:

1) Instant Member Search (the searches conducted at the top of the page) is now able to search the entire LinkedIn database. Previously, instant search only searched for 1st and 2nd tier connections. LinkedIn also claims that searches are now more relevant, faster, and more efficient.

instant search

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2) LinkedIn will now be able to develop further search functionalities which will be able to explore the entire LinkedIn economic graph. The example searches provided as examples are very similar to Facebook graph searches (not surprising given that Sankar previously worked on search quality/ranking issues for Facebook). See below for the example economic graph searches:

Screen Shot 2014-06-13 at 9.57.18 AM

If you’re looking for more technical details, read the entire post from LinkedIn.

Jeremy Roberts, SPHR, is VP, Customer Experience at HiringSolved. He is the previous Editor of SourceCon. Prior to joining the ERE Media team, he spent over a decade working as a recruiter, sourcer, and sourcing manager. This time was spent in diverse environments, including third party agency settings (retained and contingent), recruitment process outsourcing (RPO) providers, and internal corporate HR departments. His previous employers include the MHA Group, Ajilon Finance, Korn Ferry Futurestep, Raytheon Space and Airborne Systems, and Randstad Sourceright, US. He resides in Corinth, TX with his wife and 3 children.


2 Comments on “LinkedIn and the Galene Search Update

  1. Can you use Boolean operator “NOT” so you can screen out anyone who claims to be a guru or a ninja?

  2. If anyone figures out how to get this early, I’m all ears. I don’t see anything but the Semantic search.

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