Google’s ‘People Also Ask’ Patent

Google Related Questions

Google’s People Also Ask Questions Patent

When you search at Google, the answers you receive sometimes now include additional questions, that often have the label above them, “People Also Ask.” I was curious if I might be able to find a patent about these questions, and I saw that these “people also ask” questions were sometimes referred to as “related questions.”

An article at Moz today on the topic was interesting: Infinite ‘People Also Ask’ Boxes: Research and SEO Opportunities. The answers about how these related questions are decided upon seem to have a simpler origin as described in Google’s patent, but it is interesting comparing the ideas from that post with the patent.

I searched through Google patent search for “related questions” and I came up with a patent named, “Generating related questions for search queries”. When I looked at the screenshots that accompanied the patent, they appeared to be very similar to the “People also ask” type questions Google shows us today in search results.

Continue reading “Google’s ‘People Also Ask’ Patent”

Entities in the Google Knowledge Graph Search API for Google

Exploring The Google Knowledge Graph Search API

Google-favicon-2015

The Google Knowledge Graph Search API on a query for Google shows the following Entities and results scores for them. I thought they were diverse enough to be interesting and worth sharing. A couple of the ones listed seem odd, such as the Indian Action movie. “Thuppakki” and the Town in Kansas,”Topeka.” (It seems like there is a song titled, “Google Google” in the film Thuppakki, and in 2010 Topeka renamed itself “Google” to try to attract Google Fiber to the area.) We are told by Google that “Results with higher result scores are considered better matches.”

These are the Google Knowledge Graph Search API results on a search for Google:

Google “resultScore”: 292.863342
Google Chrome “resultScore”: 51.392109
X “resultScore”: 51.392109
Googleplex “resultScore”: 44.052853
Google China “resultScore”: 30.75222
Google Lively “resultScore”: 30.75222
DoubleClick “resultScore”: 29.141159
GV “resultScore”: 28.957876
Thuppakki “resultScore”: 28.693569
Google Store “resultScore”: 26.077885
“Google Japan” “resultScore”: 24.272602
DeepMind Technologies “resultScore”: 24.115602
Topeka “resultScore”: 23.718664
Rich Miner “resultScore”: 21.961121
Google Capital “resultScore”: 21.048887
Google Hacks “resultScore”: 21.003328
“Google Korea” “resultScore”: 20.818398
Barney Google and Snuffy Smith “resultScore”: 20.384176
Verily Life Sciences “resultScore”: 19.65727
Patrick Pichette “resultScore”: 19.614473

Continue reading “Entities in the Google Knowledge Graph Search API for Google”

Google Patents Context Vectors to Improve Search

For example, a horse to a rancher is an animal. A horse to a carpenter is an implement of work. A horse to a gymnast is an implement on which to perform certain exercises.
For example, a horse to a rancher is an animal. A horse to a carpenter is an implement of work. A horse to a gymnast is an implement on which to perform certain exercises.

One of the limitations of information on the Web is that it is organized differently at each site on the Web. As a newly granted Google patent about Context Vectors notes, there is no official catalog of information available on the internet, and each site has its own organizational system. Search engines exist to index information, but they have issues, as described in this new patent that make finding information challenging.

Limitations on Conventional Keyword-Based Search Engines

Continue reading “Google Patents Context Vectors to Improve Search”

Selecting Entities on Sites and Performing Tasks On Them Through Google

Visitors to a website may want to perform certain actions related to Entities (specific places or people or things) that are displayed to them on the Web.

For example, at a page for a restaurant (an entity), a person viewing the site may want to create a reservation or get driving directions to the restaurant from their current location. Doing those things may require a person to take a number of steps, such as selecting the name of the restaurant and copying it, pasting that information into a search box, and submitting it as a search query, selecting the site from search results, determining if making a reservation is possible on the site, and then providing information necessary to make a reservation; getting driving directions may also require multiple steps.

Using a touch screen device may potentially be even more difficult because the site would possibly then be limited to touch input.

A patent granted to Google this week describes a way to easily identify an entity such as a restaurant on a touch device, and select it online and take some action associated with that entity based upon the context of a site the entity is found upon. Actions such as booking a reservation at a restaurant found on a website, or procuring driving directions to that site, or other actions could be easily selected by the user of a site.

Continue reading “Selecting Entities on Sites and Performing Tasks On Them Through Google”

The Evolution of Search

I just returned from a few days in Las Vegas and the Pubcon Conference.

I had the chance to see some great presentations and talk to a number of interesting folks, and the company that I am the Director of Search Marketing at, Go Fish Digital won a US Search Award for Best Use of Search for Travel/Leisure, for a campaign we did for Reston Limo.

I wanted to share my presentation from the conference here as well.

Continue reading “The Evolution of Search”

How Google might Disambiguate Entities with the Same Names in Queries and Pages

Last year I wrote a post titled Google on Finding Entities: A Tale of Two Michael Jacksons. The post was about a Google patent that described how Google might tell different entities apart that shared the same name. The patent in it was filed in 2012 and granted in 2014. Google was also granted a new patent on how it might disambiguate entities this week, which was originally filed in 2006. It is worth looking at this second one, given how important understanding entities is to Google.

Webb Telescope Mirrors Arrive at NASA Goddard, NASA Goddard Space Flight Center, Some Rights Reserved.

It contains a pretty thoughtful approach to understanding and distinguishing between different entities within documents and queries.

Continue reading “How Google might Disambiguate Entities with the Same Names in Queries and Pages”