Three years after Google rolled out the first version of its Panda algorithm, Google has been granted a patent for it by the US Patent and Trademark Office.
Navneet Panda and Vladimir Ofitserov are listed as the inventors of the algorithm, which explains how Panda got its name. It’s interesting to note, before Panda launched it was rumored to be called “Farmer” because it was designed to target content farms. It wasn’t until Google’s Amit Singhal was asked about it in a Wired interview that we learned the algorithm would be called Panda.
Another interesting thing to note about the patent is it was filed for in 2012, quite a while after Panda was rolled out, and not granted until 2014.
Further reading into the details of the patent indicate how it is designed to understand abbreviations for domains. For example, a search for “SEJ” may return a result for the Search Engine Journal homepage because Panda is designed to understand how domains are referred to by their users.
Here’s what it says in the patent description about that:
… if the system has data indicating that the terms “example sf” and “esf” are commonly used by users to refer to the resource whose URL is “http://www.sf.example.com,” queries that contain the terms “example sf” or “esf”, e.g., the queries “example sf news” and “esf restaurant reviews,” can be counted as reference queries for the group that includes the resource whose URL is “http://www.sf.example.com.”
There are also some interesting sections about links, specifically how a user navigates from one page to another. There is a section of text that indicates Panda considers whether or not the page being linked to is a navigational result for the anchor text being used, “The system can determine whether a query is navigational to a resource by accessing data that identifies queries that are classified as navigational to each of a number of resources.”
A lot of the text is admittedly hard to understand if you’re not an expert when it comes to reading patents, but it’s worth looking through if you want to try and gain a deeper understanding of the Panda algorithm.