On October 1, 2019, I wrote a few continuation patent replace to Google’s Common Seek Effects. It was once the fourth time that exact patent had gotten up to date. I wrote about it beneath the put up title – Google’s New Common Seek Effects. It is smart to look what new adjustments have came about with a brand new continuation patent in Google Common Seek 2200.
The inventors indexed at the patent are the similar as at the unique model of the patent, and the outline seems equivalent. The adjustments are to the claims phase of the patent, which the prosecution officials on the USPRO have a look at when deciding whether or not to grant or deny a continuation patent.
A continuation patent will suppose the patent’s submitting date or patents that it continues, with the claims phase appearing off new processes in what the patent excludes others from doing.
So preferably, we must evaluate the most recent claims and the older ones. I’ve reached the primary claims from the primary 4 patent variations. What information language or processes are on this 5th model of the patent? This is the primary model:
United States Patent 11,314,822
Granted: April 26, 2022 – Interface for a common seek
Inventors: Bret S. Taylor, Marissa Ann Mayer, Orkut Buyukkokten
A seek engine might seek for a consumer seek question over a number of imaginable seek classes. For instance, the quest question is also carried out for common internet paperwork, photographs, and information paperwork. The hunt engine ranks classes in accordance with the quest question and the information returned for each and every sort and gifts the quest effects to the consumer by means of type. Upper rating classes is also given extra prominently than lower-ranking classes.
This is the primary declare of this newest model of Google’s Common Seek Patent:
What is alleged is:
1. A pc-implemented means comprising:
- Receiving a seek question in accordance with voice popularity of consumer enter submitted via a virtual assistant
- Figuring out a relevance ranking for each and every explicit class of responses to the quest question amongst a couple of other classes of responses to the quest question, the relevance ranking for each and every class signifies the relevance of responses to the quest question that corresponds to the precise class
- Offering, based on the quest question, an output that specifies related classes of responses to the quest question, together with
- Organizing presentation of the output such that the a couple of other classes get supplied in a specified order in keeping with the relevance ratings that point out the relevance of each and every of the actual classes in regards to the seek question
- Together with, within the output for each and every of 2 or extra classes, seek effects related to each and every of the 2 or extra other classes.
I’m additionally going to put up the primary declare of the sooner model of the Google Common Seek patent to make the 2 more uncomplicated to check:
The First declare from the ultimate continuation model os Google’s Uuniversal Seek patent (Might 17, 2016) seems like this:
1. A pc-implemented means comprising:
- Receiving a seek question
- Acquiring knowledge indicating a couple of units of sources aware of the quest question, each and every of the more than a few phases of sources getting categorised as corresponding to another class of sources
- Figuring out a relevance ranking for each and every of the other classes, the relevance ranking for each and every class signifies the relevance of the set of sources comparable to the category in regards to the seek question
- Offering, based on the quest question, a seek effects web page that gifts seek effects figuring out sources from the a couple of units of sources, together with
- Organizing the quest effects for show such that seek effects comparable to other classes get supplied in respective spaces that experience places made up our minds in keeping with the relevance ratings for the more than a few varieties that point out the relevance of the person units of sources in regards to the seek question
- Together with, within the respective spaces supplied for each and every of 2 or extra of the other classes, seek effects which might be related to the 2 or extra other classes, in which a second-most suitable selection has fewer seek effects
- The hunt effects web page gifts a maximum related class in accordance with probably the most related class is extra related to the quest question than the second one maximum related class
What’s New in Google Common Seek 2200?
1. The brand new claims seek advice from a “seek question in accordance with voice popularity of consumer enter submitted via a virtual assistant.” This declare is the primary connection with voice popularity or a virtual assistant.
2. The older declare specifies that the selection of seek effects proven to a searcher has fewer seek effects than previous classes of seek effects that may seem above it. The newest model of the claims doesn’t include the “fewer” effects from the consequences that seem above it. Why is that this vital? The patent doesn’t say, however it kind of feels an organizing concept in the back of the patent now.
3. Once more, this patent doesn’t checklist the several types of leads to SERPs based on a question. A declare from the 2008 model of the patent advised us particularly concerning the results in Common Seek effects: “The process of declare 1, the place the file classes come with a minimum of one in every of a information class, a picture class, or a product class.” That’s the ultimate time that Google has indexed several types of effects that may seem in Common seek effects.
5. There may be extra language about voice popularity within the claims for the most recent model of the Google Common Seek 2200 patent. It tells us that: “11. The machine of declare 8, in which offering the output that specifies the related class of responses incorporates offering the output via a speaker.” It can give those seek effects via a speaker. So it sounds as if that Google is updating this Common Seek Effects 2200 patent to be useful when getting used as a part of a virtual assistant machine.
This seems to slot in with the motion in opposition to conversational seek (Lamba) that Google has introduced and seek effects which might be tales and conversations, and extra automatic assistant patents from the quest engine.