Hummingbird search algorithm introduced by Google

Google has introduced a major update to its search algorithm.

TL;DR?  Better natural language processing capabilities, the ability to filter items easily, the ability to compare items easily, and a continued focus on mobile results.

Yet again the #semanticweb writ large in this latest evolution of Google's search algorithm and capabilities.

Other resources, aside from the TechCrunch article from +Greg Kumparak  linked in the tile:

Fifteen years on—and we’re just getting started
The official announcement from Google, although it doesn't use the word "Hummingbird"
http://bit.ly/1h5XKNi

Meet Hummingbird: Google Just Revamped Search To Handle Your Long Questions Better - +Robert Hof / Forbes
http://onforb.es/1h5YxOe

Google Reveals "Hummingbird" Search Algorithm, Other Changes At 15th Birthday Event - +Danny Sullivan / SEL
http://selnd.com/1bfq5Ub

Google Reveals Major Update to Search Algorithm - +Kurt Wagner / Mashable
http://on.mash.to/190EGkJ

Interesting point made on TechCrunch article:
Despite a good amount of questioning from the audience on just how Hummingbird worked, Google avoiding getting too technical. While they did say that this was the biggest overhaul to their engine since the 2009 “Caffeine” overhaul (which focused on speed and integrating social network results into search) and that it affects “around 90% of searches”, there wasn’t much offered in terms of technical details.

As Danny Sullivan points out in his live blog:
I'm confused. Caffeine was a new indexing system, not an new algorithm

Me too.  Danny provides a bit more detail based on answers to his question about this, and I'm sure we'll hear more shortly.  The gist of this is probably "the biggest single change since Caffeine" even if it's not strictly analogous.

Danny also provides a good summary of the major impacts (most typos corrected):
Gave us an opportunity, hummingbird did, to take synonyms and knowledge graph and other things Google has been doing to understand meaning to rethink how we can use the power of all these things to combine meaning and predict how to match your query to the document in terms of what the query is really wanting and are the connections available in the documents. and not just random coincidence that could be the case in early search engines.

(This is very exciting to me personally because this is exactly what I'm going to be talking about at SMX East.  Not a plug - just really a gush of gratitude to Google for doing something that pretty much supports the whole point I'll be making about #semanticseo .:)

For search marketers, even more of a reason to shift their thinking from strings to things, and to take a good hard look at search engine optimization strategy in the age of semantic search.

Oh yeah, and if you hated instant answers before because they "robbed" you of traffic to your site ... you'll be livid now.

Big +1 to +David Amerland for his cc: to me on this.

#Hummingbird  
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