PageRank Updated

PageRank Updated by Google

A popular search engine developed by Google Inc. of Mountain View, Calif. uses PageRank.RTM. as a page-quality metric for efficiently guiding the processes of web crawling, index selection, and web page ranking. Generally, the PageRank technique computes and assigns a PageRank score to each web page it encounters on the web, wherein the PageRank score serves as a measure of the relative quality of a given web page with respect to other web pages. PageRank generally ensures that important and high-quality web pages receive high PageRank scores, which enables a search engine to efficiently rank the search results based on their associated PageRank scores.

~ Producing a ranking for pages using distances in a web-link graph

A continuation patent showing PageRank updated was granted today. The original version of this PageRank patent was filed in 2006 and reminded me a lot of Yahoo’s TrustRank (which is cited by the patent’s applicants as one of a large number of documents that this new version of the patent is based upon.)

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3 Ways Query Stream Ontologies Change Search

How Query Streams Might be Used to Build Ontologies

What are query stream ontologies, and how might they change search?

Search engines trained us to use keywords when we searched – to try to guess what words or phrases might be the best ones to use to try to find something we are interested in. That we might have a situational or informational need to find out more about. Keywords were an important and essential part of SEO – trying to get pages to rank highly in search results for certain keywords found in queries that people would search for. SEOs still optimize pages for keywords, hoping to use a combination of information retrieval relevance scores and link-based PageRank scores, to get pages to rank highly in search results.

With Google moving towards a knowledge-based attempt to find “things” rather than “strings”, we are seeing patents that focus upon returning results that provide answers to questions in search results. One of those from January describes how query stream ontologies might be created from searcher’s queries, that can be used to respond to fact-based questions using information about attributes of entities.

There is a white paper from Google co-authored by the same people who are the inventors of this patent published around the time this patent was filed in 2014, and it is worth spending time reading through. The paper is titled, Biperpedia: An Ontology for Search Applications

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Related Questions now use a Question Graph and are Joined by ‘People Also Search For’ Refinements

I recently bought a lemon tree and wanted to learn how to care for it. I started asking about it at Google, which provided me with other questions and answers related to caring for a lemon tree. As I clicked upon some of those, others were revealed that gave me more information that was helpful.

Last March, I wrote a post about Related Questions at Google, Google’s Related Questions Patent or ‘People Also Ask’ Questions.

Related Questions Patent Updated to Include a Question Graph

As Barry Schwartz noted recently at Search Engine Land, Google is now also showing alternative query refinements as ‘People Also Search For’ listings, in the post, Google launches a new look for ‘people also search for’ search refinements. That was enough to have me look to see if the original “Related Questions” patent was updated by Google. It was. A continuation patent was granted in June of last year, with the same name, but updated claims

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Google’s Mobile Location History

If you use Google Maps to navigate from place to place, or if you have agreed to be a local guide for Google Maps, there is a chance that you have seen Google Mobile Location history information. There is a Google Account Help page about how to Manage or delete your Location History. The location history page starts off by telling us:

Your Location History helps you get better results and recommendations on Google products. For example, you can see recommendations based on places you’ve visited with signed-in devices or traffic predictions for your daily commute.

You may see this history as your timeline, and there is a Google Help page to View or edit your timeline. This page starts out by telling us:

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Does Google Use Latent Semantic Indexing?

Railroad Turntable Sign
Technology evolves and changes over time.

There was a park in the town in Virginia where I used to live that had been a railroad track that was turned into a walking path. At one place near that track was a historic turntable where cargo trains might be unloaded so that they could be added to later trains or trains headed in the opposite direction. This is a technology that is no longer used but it is an example of how technology changes and evolves over time.

Latent Semantic Indexing is Old Technology

Some people doing SEO claim that Google is using Latent Semantic Indexing because they believe that by saying that they are saying that Google is using synonyms and semantically related words. But Latent Semantic Indexing is an old patented technology that doesn’t just mean that Google is using synonyms and semantically related words. Google does like synonyms and Semantics, but they don’t call it Latent Semantic Indexing, and for an SEO to use those terms can be misleading, and confusing to clients who look up Latent Semantic Indexing and see something very different.

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Google Targeted Advertising, Part 1

Google targeted Ads

One of the inventors of the newly granted patent I am writing about was behind one of the most visited Google patents I’ve written about, from Ross Koningstein, which I posted about under the title, The Google Rank-Modifying Spammers Patent It described a social engineering approach to stop site owners from using spammy tactics to raise the ranking of pages.

This new patent is about targeted advertising at Google in paid search, which I haven’t written too much about here. I did write one post about paid search, which I called, Google’s Second Most Important Algorithm? Before Google’s Panda, there was Phil I started that post with a quote from Steven Levy, the author of the book In the Plex, which goes like this:

They named the project Phil because it sounded friendly. (For those who required an acronym, they had one handy: Probabilistic Hierarchical Inferential Learner.) That was bad news for a Google Engineer named Phil who kept getting emails about the system. He begged Harik to change the name, but Phil it was.

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