Bill Slawski
Bill Slawski can be found online at:
Twitter: bill_slawski
LinkedIn: https://www.linkedin.com/in/slawski/
Facebook: https://www.facebook.com/bill.slawski
With more than 24 years of SEO experience and a Juris Doctor Degree, Bill Slawski is the foremost expert on Google’s patents as related to SEO. Bill is the Editor of SEO by the Sea, a prominent search engine optimization blog, where he is the author of over 1,300 posts.
Bill’s experience includes Fortune 500 brands and some of the largest websites in the world. Bill is a contributing author for Moz, Search Engine Land, and Search Engine Journal. In 2014-2021, he spoke at industry-leading conferences about topics including search engine algorithms, universal and blended search, personalization in search, search and social, and duplicate content problems, structured data, and schema
A Note-Keeping Application From Google
Google Assistant As a Note Keeping Application A note-keeping application and other computer applications enable a searcher to create note entries that include content explicitly set by the searcher. For example, the searcher may create a note of “call Bob.” Further, some computer applications may enable limited searching of the searcher-created notes. This patent refers […]
Author Scores for Recommendations at Google
How Are Author Scores Generated by Google? Google’s patent covers ways to recommend posts in a messaging service to searchers who do not subscribe to posts and generates author scores. Interestingly, this patent refers to author scores and refers to AuthorRank a few times. I first wrote about Agentrank in 2007, and over time it […]
Rewriting Keywords at Google for Paid Search
Expanding Queries by Rewriting Keywords Google’s patent is from March 9, 2021. It covers rewriting keywords to expand queries and return a wider range of search results in response to what a searcher has searched for. The patent appears to cover paid search results, even though the keyword rewriting approach has been in organic SEO […]
Original Content and Original Authors Identified by Google
Original Content and Text Processing Searchers search for relevant documents using a search engine. Those are in a body of documents. The search engine returns a list of documents to respond to a search query. Search results order depends on the relevance, or rank, of each document. How does the search engine identify original content? […]
How to Blend and Rerank Search Results at Apple
Another Sign that Apple Search is On Its Way Apple appears to be working towards developing a search engine. I have written a few posts about patents developed at Apple showing them getting into areas that Google is better known for. A newer Apple patent shows that Apple has developed a way of re-ranking search […]
Relevant Search Results for Longer Documents at Google
Ranking of Books and Other Long Documents in Search Results A newly granted Google patent tells us about information retrieval and searcher interfaces for relevant search results for a query. It focuses on longer organic content such as books, or newsletters, or catalogs in search results. I have seen results from Google Books mixed in […]
Spoken Queries Using Language Models
Automated Speech Recognition using Use of Class-Based Language Models to Transcribe Speech to Text The Google n-gram viewer program from the top image shows that Pittsburgh (or Pittsburg) words can be spelled more than one way.) Using language models is one of the complexities behind spoken queries. Understanding how Google handles vocal queries that are […]
Local Predictive Search Suggestions From Google
Predictive Search Suggestions Based on Location This patent is about providing information relevant to search queries. Internet search engines identify resources, e.g., Web pages, images, text documents, and multimedia content, in response to queries submitted by searchers. Then, they work to present information about those resources in a useful manner to the searchers. One assumption […]
Natural Language Queries in Spreadsheets at Google
Answering Natural Language Queries From Spreadsheets Imagine a site owner shares information on the web using spreadsheets or databases. I wrote a related post at Natural Language Query Responses. We see Google with patents focused on answering natural language queries using data tables. Today’s blog post is about answering questions about spreadsheets or databases written […]
Machine Learning For a Ranking Model
Machine Learning at Google This Google patent is about training a machine learning model to rank documents in response to search queries. Online search engines such as Google rank documents in response to search queries to present search results filled with documents that are responsive to a search query. Search engines usually show search results […]