I was excited to see a Google Patent granted this past Thursday, which describes how Google may rank pages in part based upon user feedback (clicks) in response to rankings for those pages. The patent tells us that this kind of identifying of a user’s needs and determining which documents are returned that might be most useful to a searcher can involve “a fair amount of mind-reading—inferring from various clues what the user wants.” But, we’ve been told recently by a Google Spokesperson that such clues can be misleading. I thought it was still worth pointing the patent out.
Some clues may be user specific, the patent authors tell us, and when a searcher searches from a mobile device, and Google know the location of that device, the results returned “can result in much better search results for such a user.” That does make sense.
A Google patent application published in the last week describes how Google might be using Mobile data from phones to map indoor spaces, combining the technologies behind Behavio, with traffic monitoring from Zipdash to better understand spaces that many people navigate through while carrying a mobile device that connects to the internet with wireless signals and carries sensor data that can indicate the location and movements of those devices.
The patent tells us that current approaches to determine indoor locations of mobile devices are based on interior scans of wireless access points. Theses scans could be used to build a database that can model an indoor space by determining locations of the access points and their corresponding signal strengths at those locations. To create a database like this, an indoor wireless location provider would have to conduct site surveys at selected locations.
Sometimes, I run across a patent that provides details on things that Google might do, but only hints at whether or not it might actually be implemented. A few years back in 2007, I wrote about a Google patent for Agent Rank, which described reputation scores for authors (to be used as an alternative to PageRank), and looked like an important part of Google’s social network, Google+. It was referred to in the patent as “Agent Rank” and people commenting upon it started referring to it as “Author Rank”.
It seemed like it was a good description of how some people whom you may have connected with in Google+ were showing up in response to queries they had some expertise within. There may have been issues with Google’s version of Agent Rank that the search engine wanted a second bite at. Google has since removed the Photos that were showing up for authors whom you might be connected to, who may have been highly ranked, seemingly based upon a reputation score, for a topic related to a query that you might perform.
There were people who wrote that while this authorship markup was removed, and author photos associated with it, the author rank scoring system that came with it was still around, like this Search Engine Land article: Google Authorship May Be Dead, But Author Rank Is Not.
This patent application from last week describes a search system query processing for queries that are questions.
Queries may be responded to with a wide variety of resources, such as image files, audio files, video files, and web pages. A search engine may identify resources in response to queries submitted by searchers and attempt to provide information in response “in a manner that is useful to the users.”
Searchers may look for an answer to a specific question, rather than a listing of links to other pages and resources.
We’ve all read about Google working to build self-driving cars, and I’ve written about Google building Google Maps programs to help people navigate to different places.
A Google patent application published this week takes a closer look at computers in cars, and the many sensors that are connected to those, and it discusses how automotive computing systems that include such things as:
…network based applications including navigation, voice search, media streaming capabilities, and the like.
The patent mentions On board diagnostics (OBD) standards in the automotive industry were made became available with engine computer systems that showed up in the 1980s.
So, one of the big questions in SEO these days is why some queries end up triggering Answer Boxes in search results, and others don’t.
A Recent Bloomberg article explores how Google might use machine learning to answer questions, titled, Google’s New AI Can Answer Dumb IT Questions or Tell You the Meaning of Life. I came across the article after having read a patent application at Google that covered similar ground.The point behind the patent was to identify sources of answers to queries, that are in the shape of Answer Boxes, as seen in this search result:
As this patent application tells us, sometimes searchers are looking for answers to their queries, rather than a list of URLs:
Barbara and I have been looking at a lot of patents while preparing for the presentation, and one of the topic areas that we were going to discuss was Quality Scores, since one of the patents that mentions adding “Buy Now” buttons to paid search listings in search results, may do so only if the sites being considered to show buy now buttons have a high enough Quality Score associated with them.
While preparing, Barbara pointed out another patent to me that focuses upon low quality scores. It describes how a site might lose traffic if ranking scores for links pointed to it are below a certain threshold.