Author Vectors Patent
Author vectors patentis a Google patent filed in 2018, which uses neural networks that can distinguish who writes content based on text classification. Author classification could some day be an influential ranking factor to determine what popular content is by distinguished authors in the SERPs (search engine result pages). Author classification has been used in libraries for decades to identify writing styles you may prefer to follow, so it makes sense to use it in search results.
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How Location Queries affect Search Results
People don’t want to know where businesses are across the country (unless they are planning a trip), but they want to know what is immediately close to them to fulfill that search intent. This is why local SEO is a vital aspect of your digital strategy.
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Google’s Reasonable Surfer Model
Google’s Reasonable Surfer Model is a search engine algorithm that promotes transparency and fairness in the ranking of websites. This model aims to provide more helpful information for searchers by considering content relevance, link quality, and user signals. This post will explore how Google uses these factors to rank websites in their search results pages.
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Google’s Rich content for query answers Patent
Google’s “Rich content for query answers” patent is designed to provide rich answers to questions in the SERPs using media (audio, video, images) to supplement a featured snippet.
The patent aims to provide an answer using visual or audible results, not just text. These rich snippets will increase a positive user experience and reduce the time it takes to find solutions.
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Published on: 2021-04-16
Updated on: 2021-05-28