A weekly short discussion for SEOs that examines specific Google patents with discussions led by NotebookLM to make search-relevant patents easier to understand...
Search results are increasingly contextual. Recognising the context of a query and the user leads to better search results and user experience. This Query Composition Systems patent is a peace of the puzzle to handle this challenge.
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14:34
Predicting Latent Structured Intents from Shopping Queries
This week we are checking out Predicting Latent Structured Intents from Shopping Queries which is how Google uses an AI framework to extract from ambiguous shopping queries
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8:54
Systems and Methods for Improving the Ranking of News Articles
Today we are looking at the 'Systems and Methods for Improving the Ranking of News Articles' patent which outlines a method to rank news articles based on the quality of their sources, improving the relevance and reliability of search results.
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26:10
Systems and Methods for Using Document Activity Logs to Train Machine-Learned Models for Determining Document Relevance
We discuss the patent that outlines a cutting-edge approach to leveraging document activity logs for training machine-learned models. It highlights how this innovation enhances the ability to determine document relevance, streamlining information retrieval and improving user experiences.
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12:52
Providing Search Results Based on a Compositional Query
In this episode, we take a long look at a system for generating search results from compositional queries. It highlights how this method combines multiple query elements to refine and contextualize searches, enabling users to achieve more precise and relevant results efficiently.
A weekly short discussion for SEOs that examines specific Google patents with discussions led by NotebookLM to make search-relevant patents easier to understand.
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