How Google uses NLP to better understand search queries, content
Learn the role that natural language processing plays in making Google search even more semantic and context-based.
Learn the role that natural language processing plays in making Google search even more semantic and context-based.
Learn how to get the best out of the relationships between words, topics and pages to maximize your SEO results.
AI will completely change SEO as we know it. From optimization to link building, it will significantly impact every aspect of SEO.
Learn the relationship between entities and expertise, authority and trust, or E-A-T evaluation of authors, publishers and companies.
Want to understand how machine learning impacts search? Learn how Google uses machine learning models and algorithms in search.
Is MUM Google's next step toward becoming a purely semantic search engine? Learn what MUM could mean for the future of SEO.
Google Docs can automatically generate content summaries. Can it help you write a GREAT meta description? We tested it to find out.
Also, Google said they saw an 60% increase in natural language queries by searchers.
From RankBrain, Neural Matching, BERT and MUM - here is how Google uses AI for understanding language for query, content and ranking purposes.
Keywords are foundational, but entities may be the future. At SMX Next, a panel of SEO experts shows how marketers can optimize their content for entity search.
AI and its offshoots are expanding capabilities for marketers to help them scale tasks. At SMX Next, Eric Enge shows how marketers can improve their SEO campaigns with automation.
While you can’t target users or interests, you can increase your chances of ranking better in Google Discover. At SMX Next, John Shehata shared the tactics he uses to up the odds and analyze what works.
Google has also provided new details for when searches are identical to a given keyword as well as when a search isn’t identical to any of an advertiser’s keywords.
Plus, is pinning the solution to control RSAs?
Plus, the latest trends in local search: personalization and depth of content
“There is no expectation that it will become this question-answering system,” Nayak told Search Engine Land, adding that such a system is “just not useful” for complex needs.
The technology is providing Google with an efficiency advantage over competitors and helping it surface more relevant results.
Apply a strategy to each stage of the content lifecycle to see traffic come in long after you hit publish.
This might be the voice search functionality we’ve all been waiting for.
Multitasking is the key differentiator, enabling MUM to acquire knowledge, understand and generate language and interpret text, images and video all at the same time.
Plus, the business imperative behind inclusion and diversity
Some of these observations are based on the quality raters guidelines, the past core updates, and sound SEO advice.
Google is using newish language understanding models specific to leveraging conversational context for these search features.
AI-generated copy isn't perfect, but these tools can churn out ideas and inspiration in a matter of seconds.
How Google leverages BERT depends on the use of the term ‘Passage Indexing’ (although it’s identified as a ranking update).
Google’s recent updates provide SEOs with more freedom to focus on users instead of bots.
Building the data bridge between online and offline.
Google announced numerous improvements made to search over the year and some new features coming soon.
Intelligent answers and semantic highlighting are also rolling out to more markets.
Study by SEMrush found only 1% overlap in answers to the same voice queries across platforms.
Using a code-free deep learning toolkit model to review grammar in your posts and could be used as one of several proxies for content quality.
The yes/no summary uses natural-language modeling and comes with a carousel of sources.
The devices have reached 50% of US homes, but fallen flat as a channel
A new study looks at how contextual relevance of ads to content influences consumers.
We also chatted about her career, PPC versus SEO, natural language in search and some controversial topics in Google Ads.
It is more important than ever to update your research methods since the release of BERT and the evolution of natural language processing.
From core updates to BERT, here are the big algorithm changes that shook up search rankings in 2019.
The capability was introduced previously on Google Home and smart displays.
The algorithm was first introduced to search in October.
The natural language processing capabilities are now applied to all Bing queries globally.