I thought this was an interesting question to ask people because I think it’s often misunderstood. Google treats content found at different URLs as if it is different content, even though it might be the same, such as in the following examples:
The ultimate goal of any spam detection system is to penalize “spammy” content.
~ Reverse engineering circumvention of spam detection algorithms (Linked to below)
Four years ago, I wrote a post about a Google patent titled, The Google Rank-Modifying Spammers Patent. It told us that Google might be keeping an eye out for someone attempting to manipulate search results by spaming pages, and Google may delay responding to someone’s manipulative actions to make them think that whatever actions they were taking didn’t have an impact upon search results. That patent focused upon organic search results, and Google’s Head of Web Spam Matt Cutts responded to my post with a video in which he insisted that just because Google produced a patent on something doesn’t mean that they were going to use it. The video is titled, “What’s the latest SEO misconception that you would like to put to rest? ” Matt’s response is as follows:
I’m not sure how effective the process in that patent was, but there is a now a similar patent from Google that focuses upon rankings of local search SEO results. The patent describes this spam problem in this way:
As we approach the celebration of the 4th of July, I thought it might be interesting to share a request for information made to the US Federal Register and a post on the Whitehouse blog. The US government is interested in what Artificial Intelligence might mean to the people of the United States, and how we could learn about it more. To find out, they are asking for comments by July 22, 2016.
When I was in high school, one of the required classes I had to take was a shop class. I had been taking mostly what the school called “enriched” courses, or what were mostly academic classes that featured primarily reading, writing, and arithmetic. A shop class had more of a trade focus. I was surprised when the first lesson on the first day of my shop class was a richer academic experience than any of the enriched classes I had taken.
– What other people are searching for, including trending searches. Trending searches are popular stories in your area that change throughout the day. Trending searches aren’t related to your search history.
– Relevant searches you’ve done in the past (if you’re signed in to your Google Account and have Web & App Activity turned on).
Note: Search predictions aren’t the answer to your search, and they’re not statements by other people or Google about your search terms.
Google is possibly most well known for the patenting of an algorithm that sorted and ordered search results based upon a metric known as PageRank, named after Google Co-Founder Lawrence Page, while he was a student at Stanford University. Yahoo started off as a Web Directory, which became a Search Engine, and the patent it might be most well known for is one that it purchased from Overture (Originally Goto.com), and successfully sued Google with (winning a settlement out of the litigation) which describes paid search. That patent appears to have been assigned by Yahoo, along with a number of other patents last month.
On April 18th, 2016 an assignment was recorded at the United States Patent and Trademark Office (USPTO) on a transaction that appears to have been executed on April 18th, 2016 involving the assignment of 2648 patents from Yahoo! Inc. to Excalibur IP, LLC. It’s possible that name is made up to hold the patents temporarily. The address that the assignment indicates is Excalibur’s is “701 FIRST AVENUE SUNNYVALE, CALIFORNIA UNITED STATES OF AMERICA 94089”. A search for that address points to the headquarters of Yahoo! as we see in the knowledge panel below, so the actual purchaser appears unknown.
Systems and methods consistent with the principles of the invention may provide a reasonable surfer model that indicates that when a surfer accesses a document with a set of links, the surfer will follow some of the links with higher probability than others. This reasonable surfer model reflects the fact that not all of the links associated with a document are equally likely to be followed. Examples of unlikely followed links may include “Terms of Service” links, banner advertisements, and links unrelated to the document.
Google’s original PageRank algorithm is based upon what its inventor referred to as the Random Surfer model, where it ranked pages on the Web based upon a probability that a person following links at random on the Web might end up upon a particular page:
The rank of a page can be interpreted as the probability that a surfer will be at the page after following a large number of forward links. The constant α in the formula is interpreted as the probability that the web surfer will jump randomly to any web page instead of following a forward link.
Do you search through Google on your phone? How do you know whether or not Google is watching you as you do and keeps on eye on whether or not you like the results you receive during your searches? Could Satisfaction with search results be a ranking signal that Google may use now, or in the future?
A newly published Google patent application describes technology that would modify scoring and ranking of query results using biometric indicators of user satisfaction or negative engagement with a search result. In other words; Google would track how satisfied or unsatisfied someone might be with search results, and using machine learning, build a model based upon that satisfaction, raising or lowering search results for a query. This kind of reaction might be captured using a camera on a searcher’s phone to see their reaction to a search result, as depicted in the following screenshot from the patent:
This satisfaction would be based upon Google tracking and measuring biometric parameters of a user obtained after thst search result is presented to the user, to determine whether those may indicate negative engagement by the user with a search result.