Google Search Staff Changes

Amit Singhal, Google’s Senior Vice President of Search, is stepping down after 15 years with Google, to do more in philanthropy and have time for family.

Amit Singhal, The Head Of Google Search, To Leave The Company For Philanthropic Purposes, Barry Schwartz, Search Engine Land

John Giannandrea is the new head of search. He had created MetaWeb, which Google acquired in 2010 and used as the basis for Knowledge Graph. Expect to see further emphasis on machine learning and artificial intelligence.

Meet Google’s new search king, Jillian D’Onfro, Business Insider (Feb 3)

Three top search engines

For people new to using general web search engines this article is good overview of the main players: Google, Bing, and Duckduckgo. Yahoo and Ask are mentioned and dismissed – rightfully so.

Which Search Engine Should You Be Using Today?, Ben Stegner, Make Use Of (Dec 11, 2015)

In reviewing Google, Stegner stresses personalized search and doesn’t describe Google’s increasing strength in working with entities and concepts. However, he does note some points of weakness in Bing compared to Google.

RankBrain here to stay

Ranking rules at Google have been changing in order to deliver more “answers” based on understanding of query and of sources. It’s called RankBrain. Not everyone is happy.

On-Page SEO and RankBrain: Continue Writing for Humans and Optimizing for Search Engines, David Farkas, UpperRanks (Dec 1)

It’s very much harder to understand and exploit that old style keyword matching.

” Is there some type of RankBrain score hat might assess quality? Perhaps, but it seems much more likely that RankBrain is somehow helping Google better classify pages based on the content they contain. RankBrain might be able to better summarize what a page is about than Google’s existing systems have done.”

Searching Google’s Country Versions

Google is making it harder to search country versions of its databases other than your own.

Google Drops Change Location Search Filter From Search Results, Barry Schwartz, Search Engine Land (Dec 1)

Schwartz reported, ” A Google spokesperson told us this feature was intentionally removed last week. Google said, “it was getting very little usage, so we’re focusing on other features.””

Which I find infuriating. Low use for removing a feature is not a good reason.

Alternatives

There is still the Chrome extension for SEO Global search.

For general use, try Disconnect – search.disconnect.me – it ensures anonymity and you can adjust the country.

Future of search as seen by Google

In the speculations about the future, web search and Google are sure to be on the agenda. At the Futuropolis conference in France, Behshad Behzadi, director of search innovation at Google’s Zurich lab, revealed Google’s goal — “The future of search is to try to build the ultimate personal assistant.”

The 4 things Google believes are key to the future of search, Chris O’Brien, VentureLink (Nov 30)

He identified four aspects for rapid change – all of which are underway now.

  1. voice search – linked to natural language
  2. use of context to get better results
  3. location based searches especially for mobile
  4. personal information and many supportive features.

Google’s RankBrain and Entity Analysis

Kristine Schachinger at Search Engine Land tackles the relationship between Google’s RankBrain use machine learning and the entity analysis Google developed in the Knowledge Graph.

How RankBrain Changes Entity Search (Oct 29)

Key section below  – but you will really want to read the entire article yourself.

So while Google can understand known entities and relationships via data definitions, distance and machine learning, it cannot yet understand natural (human) language. It also cannot easily interpret attribute association without additional clarification when those relationships in Google’s repository are weakly correlated or nonexistent. This clarification is often a result of additional user input.

Of course, Google can learn many of these definitions and relationships over time if enough people search for a set of terms. This is where machine learning (RankBrain) comes into the mix. Instead of the user refining query sets, the machine makes a best guess based on the user’s perceived intent.

Google ranks results with RankBrain AI

AI has arrived at Google, after years of  corporate acquisitions and experimental work with machine learning. It’s called RankBrain and it does the following:

RankBrain uses artificial intelligence to embed vast amounts of written language into mathematical entities — called vectors — that the computer can understand. If RankBrain sees a word or phrase it isn’t familiar with, the machine can make a guess as to what words or phrases might have a similar meaning and filter the result accordingly, making it more effective at handling never-before-seen search queries.

Already RankBrain  is the third most important ranking factor.

See Google Turning Its Lucrative Web Search Over to AI Machines by Jack Clark, Bloomberg, (Oct 26) for a video and description.

Danny Sullivan provides background and details in  FAQ: All About The New Google RankBrain Algorithm [Search Engine Land, Oct 28] t RankBrian is not a new search algorithm: it is one more component (albeit important)  the overall Hummingbird search algorithm introduced a couple of years ago.

Sullivan refers to the Bloomberg article and hazards a guess that the other two top ranking signals being used by Google are 1)  links – still, in spite of problems with these, and 2) words – ie matching on the search terms. Sullivan also mentions that Google has been expanding words for several years – word variants and related words – and that these fit into selecting and ranking results.  Google also employed entity analysis in providing answers through the Knowledge Graph.

Of interest: 15% of the 300 billion queries Google handles each day are new, and being new may lead to some adjustments to algorithms by the staff of search analysts .

Among those can be complex, multi-word queries, also called “long-tail” queries. RankBrain is designed to help better interpret those queries and effectively translate them, behind the scenes in a way, to find the best pages for the searcher.

For those wishing to know more about how RankBrain works with “word vectors”, Sullivan points to a couple of papers.

Greg Finn at Search Engine Land provides another synopsis – AI has officially made it’s way into Google’s search algorithm, here’s what you should know.

Can Bing be far behind in also employing AI for its search results?