Google Patent About using ML to Surface Video in SERPs Without User Provided Data

Bill Slawski breaks down a newly granted Google patent Relevance-based image selection that sheds some light on how Google will use machine learning to provide video search results relevant to a keyword query based on features found in the videos including the ability to present one or more thumbnail images representative of the video.

When Google uses this approach, it is paying attention to all of the scenes in a video. For example, if the user enters the search query “car race,” the video search engine can find and return a car racing scene from a movie, even though the scene may only be a short portion of the movie that is not described in the textual metadata.

The process described in this patent wouldn’t require someone wanting to have a video indexed to do anything special or different. It would just mean that Google could do a better job of returning videos that might contain content that a searcher might be looking for, like a car racing scene from a movie. So with this more relevant videos can be returned for searcher’s queries based upon the actual content of those videos than just textual metadata that accompanies a video.