The SEO Patent Podcast

The Multi Source Extraction and Scoring of Short Query Answers patent dentifies a candidate passage within the search results and evaluates its accuracy using context passages from other sources. An accuracy score prediction engine is used to determine whether the candidate passage is likely to provide an accurate answer.

02-21

11:25

This week we explore Changing a Rank of a Document by Applying a Rank Transition Function, a method for detecting and mitigating rank-modifying spam in search engine results.

02-07

09:56

Presenting Search Result Information describes a system and method for presenting search results to a user. The system uses web notebooks to organise and rank search results, incorporating snippets and allowing users to create and manage their own notebooks. This US patent application describes a system and method for presenting search results to a user. The system uses web notebooks to organise and rank search results, incorporating snippets and allowing users to create and manage their own notebooks.

01-31

15:30

The Combining Search Parameters of Multiple Queries That Share a Line of Inquiry patent details a system for improving online search results by combining parameters from multiple, semantically similar user queries.

01-25

11:40

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.

01-17

14:34

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

01-10

08:54

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.

01-03

26:10

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.

12-27

12:52

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.

12-20

12:04

This episode looks at a system that evaluates multiple interpretations of a search query. It discusses how this innovative approach improves search accuracy by ranking interpretations based on relevance, providing users with results that align closely with their intended queries.

12-13

13:54

This episode examines an innovative system designed to enhance search result filtering by analyzing the content of resources. It highlights how the patented approach allows users to more precisely navigate search results, leveraging contextual filters generated from the resources themselves to refine and target their queries effectively.

12-06

11:32

The podcast episode explores Google's innovative approach to Contextual Estimation of Link Information Gain. It explores how machine learning models rank documents by assessing the novelty of information they provide to users, enhancing search efficiency and user satisfaction.

11-29

11:37

This episode explores Google's patent on 'Predicting Site Quality,' which outlines methods to estimate a website's quality using phrase-based models and frequency measures, providing insights into SEO and search rankings.

11-22

12:35

This episode dives into Google's 'Site Quality Score' patent, which details a system for evaluating the quality of websites based on user queries, interactions, and selections, and its implications for search rankings.

11-15

10:28