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Learn SEO Through Forums

July 2, 2017 No Comments

Solana Beach Farmer's Market

I had someone who was reading my previous entries in my Learning SEO series ask about using forums to learn SEO. I promised that I would write a post about the value of forums in learning SEO.

Back in 1998 I became a moderator of a couple of forums on small business and website promotion on Yahoo Groups. Those lead to me becoming a moderator at Cre8asiteforums, joining forum owner Kim Krause Berg along with a number of other moderators such as Ammon Johns and Jill Whalen.

Cre8asiteforums was (and still is) a tremendous place to talk about SEO and web design and usability and accessibility. One of my favorite individual forums on the site was one called The Website Hospital, where people would bring their site’s URL and concerns about it, and ask questions. That was were I learned a lot about auditing sites, and seeing what worked well on them, and what might need some help. This thread is a good introduction to it: Getting Started in the Website Hospital.

Here’s a thread I started in November of 2005 that was an interesting read, on SEO Myths.

Another forum that I have gotten a lot of value from over the years is one call Webmasterworld. Most of the members of this forum are practicing SEOs or siteowners, who enjoy sharing their experiences. It reminds me of a weather vane, in that people are often open with information about changes that they experience to rankings and traffic to their sites. You can see changes taking place on the Web from what they write.

Another place that can be informative about how search works is the Google Webmaster Help Forum. If you experience problems with a site, it is often a good place to search to see if anyone else has experienced something similar – it is possible that someone has, and the answers they received may help you as well.

There are other forums on the Web that focus upon SEO and Search. I’ve included the ones that I am most familiar with. There were some others that I participated on, that aren’t very active anymore. It doesn’t hurt to start off as a lurker, and learn about the customs and culture of a forum before you start participating in it. You may find some that you enjoy participating in very much.

When I started going to conferences and events after being involved in forums for a few years, I finally had a chance to meet in real life many people whom I had only met in discussions at forums. It was nice getting a chance to do so.

You can learn a lot through forums.


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Google Patents Extracting Facts from the Web

June 20, 2017 No Comments

When Google crawls the Web, it collects information about content on the pages it finds as well as links on pages. How much does it collect information about facts on the Web? Microsoft showed off an object-based search about 10 years ago, in the paper, Object-Level Ranking: Bringing Order to Web Objects..

The team from Microsoft Research Asia tells us in that paper:

Existing Web search engines generally treat a whole Web page as the unit for retrieval and consuming. However, there are various kinds of objects embedded in the static Web pages or Web databases. Typical objects are products, people, papers, organizations, etc. We can imagine that if these objects can be extracted and integrated from the Web, powerful object-level search engines can be built to meet users’ information needs more precisely, especially for some specific domains.

This patent from Google focuses upon extracting factual information about entities on the Web. It’s an approach that goes beyond making the Web index that we know Google for because it collects more information that is related to each other. The patent tells us:

Information extraction systems automatically extract structured information from unstructured or semi-structured documents. For example, some information extraction systems that exist extract facts from collections of electronic documents, with each fact identifying a subject entity, an attribute possessed by the entity, and the value of the attribute for the entity.

I’m reminded of an early Google Provisional patent that Sergy Brin came up with in the 1990s. My post about that patent I called, Google’s First Semantic Search Invention was Patented in 1999. The patent it is about was titled Extracting Patterns and Relations from Scattered Databases Such as the World Wide Web (pdf) (Skip ahead to the third page, where it becomes much more readable). This was published as a paper on the Stanford website. It describes Sergy Brin taking some facts about some books, and searching for those books on the Web; once they are found; patterns about the locations of those books are gathered, and information about other books are collected as well. That approach sounds much like the one from this patent granted the first week of this month:

In general, one innovative aspect of the subject matter described in this specification can be embodied in methods that include the actions of obtaining a plurality of seed facts, wherein each seed fact identifies a subject entity, an attribute possessed by the subject entity, and an object, and wherein the object is an attribute value of the attribute possessed by the subject entity; generating a plurality of patterns from the seed facts, wherein each of the plurality of patterns is a dependency pattern generated from a dependency parse, wherein a dependency parse of a text portion corresponds to a directed graph of vertices and edges, wherein each vertex represents a token in the text portion and each edge represents a syntactic relationship between tokens represented by vertices connected by the edge, wherein each vertex is associated with the token represented by the vertex and a part of speech tag, and wherein a dependency pattern corresponds to a sub-graph of a dependency parse with one or more of the vertices in the sub-graph having a token associated with the vertex replaced by a variable; applying the patterns to documents in a collection of documents to extract a plurality of candidate additional facts from the collection of documents; and selecting one or more additional facts from the plurality of candidate additional facts.

The patent breaks the process it describes into a number of “Advantages” that are worth keeping in mind, because it sounds a lot like how people talking about the Semantic Web describe the Web as a web of data. These are the Advantages that the patent brings us:

(1) A fact extraction system can accurately extract facts, i.e., (subject, attribute, object) triples, from a collection of electronic documents to identify values of attributes, i.e., “objects” in the extracted triples, that are not known to the fact extraction system.

(2)In particular, values of long-tail attributes that appear infrequently in the collection of electronic documents relative to other, more frequently occurring attributes can be accurately extracted from the collection. For example, given a set of attributes for which values are to be extracted from the collection, the attributes in the set can be ordered by the number of occurrences of each of the attributes in the collection and the fact extraction system can accurately extract attribute values for the long-tail attributes in the set, with the long-tail attributes being the attributes that are ranked below N in the order, where N is chosen such that the total number of appearances of attributes ranked N and above in the ranking equals the total number of appearances of attributes ranked below N in the ranking.

(3)Additionally, the fact extraction system can accurately extract facts to identify values of nominal attributes, i.e., attributes that are expressed as nouns.

The patent is:

Extracting facts from documents
Inventors: Steven Euijong Whang, Rahul Gupta, Alon Yitzchak Halevy, and Mohamed Yahya
Assignee: Google Inc.
US Patent: 9,672,251
Granted: June 6, 2017
Filed: September 29, 2014

Abstract

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for extracting facts from a collection of documents. One of the methods includes obtaining a plurality of seed facts; generating a plurality of patterns from the seed facts, wherein each of the plurality of patterns is a dependency pattern generated from a dependency parse; applying the patterns to documents in a collection of documents to extract a plurality of candidate additional facts from the collection of documents; and selecting one or more additional facts from the plurality of candidate additional facts.

The patent contains a list of “other references” that were cited by the applicants. These are worth spending some time with because they contain a lot of hints about the direction that Google appears to be moving towards.

The patent tells us that entities identified by this extraction process may be stored in an entity database, and they point at the old freebase site (which used to be run by Google).

They give us some insights into how the information extracted from the Web might be used by Google in a fact repository (which is the term they used to refer to an early version of their knowledge graph):

Once extracted, the fact extraction system may store the extracted facts in a facts repository or provide the facts for use for some other purpose. In some cases, the extracted facts may be used by an Internet search engine in providing formatted answers in response to search queries that have been classified as seeking to determine the value of an attribute possessed by a particular entity. For example, a received search query “who is the chief economist of example organization?” may be classified by the search engine as seeking to determine the value of the “Chief Economist” attribute for the entity “Example Organization.” By accessing the fact repository, the search engine may identify that the fact repository includes a (Example Organization, Chief Economist, Example Economist) triple and, in response to the search query, can provide a formatted presentation that identifies “Example Economist” as the “Chief Economist” of the entity “Example Organization.”

The patent tells us about how they use patterns to identify additional facts:

The system selects additional facts from among the candidate additional facts based on the scores (step 212). For example, the system can select each candidate additional fact having a score above a threshold value as an additional fact. As another example, the system can select a predetermined number of highest-scoring candidate additional facts as additional facts. The system can store the selected additional facts in a fact repository, e.g., the fact repository of FIG. 1, or provide the selected additional facts to an external system for use for some immediate purpose.

The patent also describes the process that might be followed to score candidate additional facts.

This fact extraction process does appear to be aimed towards building a repository that might be capable of answering a lot of questions, using a machine learning approach and the kind of semantic vectors that the Google Brain team may have used to develop Google’s Rank Brain approach.


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Learning SEO through Books

June 16, 2017 No Comments

A Path through the Batiquitos Lagoon

There are a few books and courses online that are free and really helpful when it comes to learning some of the things that will make you a better SEO. Knowledge can make a difference, and having an idea of how search engines work can possibly give you a competitive advantage over others who haven’t had a chance to learn about such resources. I’ve come across a few books that are online and free, and worth spending time with, and thought it might not be a bad idea to share them.

The first two volumes I found are ones that focus on one of the important ways that search engines understand the content of web pages, rating them based upon information retrieval scores. Having an idea of how a search engine might rank a page, based on more than just something of an understanding of how PageRank works can be really helpful.

Introduction to Information Retrieval by Christopher D. Manning, Prabhakar Raghavan and Hinrich Schütze

Modern Information Retrieval by Ricardo Baeza-Yates and Berthier Ribeiro-Neto

In the last couple of years, we have seen significant changes to how search results look at search engines. It doesn’t include knowledge panels or featured snippets or structured snippets or sitelinks, but this book does leave lots to think about when it comes to how search results are organized:

Search User Interfaces by Marti Hearst

Having a sense of how HTML and CSS and java script works can be helpful to anyone involved in SEO. This book covers the latest version of HTML which hasn’t been adopted everywhere on the Web yet, but is still worth digging into:

Dive into HTML5 by Mark Pilgrim

Online Courses and Presentations

Google has been going through a number of transformations in the past 5 years or so, and Andrew Hogue was involved in many of the changes that took place. His presentation on them is insightful:

The Structured Search Engine by Andrew Hogue:

Last September, Jeff Dean introduced us to a Google that was going to be incorporating Machine Learning into what they do – hearing some of the details behind this movement is like peeking behind the curtain:

Jeff Dean Talks Google Brain and Brain Residency:

These tutorials were pointed out to me on Twitter a couple of days ago. I started watching them, and decided quickly that they were worth sharing:

Dan Jurafsky & Chris Manning: Natural Language Processing and Lecture Slides (h/t to Victor Gras)


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Learning SEO, Summer 2017

June 10, 2017 No Comments

The Omni La Costa Resort

In January, I wrote a post titled, Advice Given to an Aspiring 14 Year-Old Entrepreneur Wanting to Learn SEO. I included in that post links to a number of pages that I thought might be helpful to someone learning SEO. On my walk this morning past the Omni La Costa Resort, I was thinking about it, and decided that it might not be a bad idea to create a Learning SEO category here, and provide more resources to help people who are learning SEO access some of the resources I come across that might help them understand more.

One that I was thinking might be really helpful is this video (SMX West 2016 – How Google Works: A Google Ranking Engineer’s Story) with Google Engineer Paul Haahr:

I’ve written about more than one patent that Paul Haahr co-invented, and he has had been involved in many important aspects of how Google operates. His insights into ranking at Google are eye opening.

Google keeps a careful eye upon the quality of their search results, and have human beings who review those results and provide feedback on them. These people are known as human quality raters, and they are provided a set of guidelines, which Google started sharing with the public. If you want to be an SEO, having an idea what those guidelines contain can be helpful; they can give you some ideas on what you might want to include on a web site. The most recent version of the quality rater guidelines came out May 11, 2017:

Search Quality Evaluators Guideline

Many people perform searches at Google everyday, entering many queries every second into a Google search box. Could we learn something from what they search for, and what words they use when they search? I wrote about that idea with a post about 4 years ago called How Google Might Use Query Logs to Find Locations for Entities. What if Google tried to learn even more from query logs? They have, and they wrote about what they’ve built from query log information, in a paper titled:

Biperpedia: An Ontology for Search Applications

One of the authors of that paper is Alon Halevy, who is the head of Structured Data at Google (the folks responsible for rich snippets, knowledge graphs, question answering, structured snippets, and table search at Google).

A tool that I have been using on almost every audit that I do is Screaming Frog, and if it isn’t in your toolbelt, it should be something that you should consider adding. It is really useful, and this page from Seer Interactive is helpful in learning how to use it effectively:

Screaming Frog Guide to Doing Almost Anything

Google is not the only search engine, and if you aren’t looking at what Microsoft is doing with Bing, you may be surprised.

I was surprised to see Microsoft come out with a really powerful knowledge graph that covers a lot of concepts in September of last year:

Microsoft Concept Graph Preview For Short Text Understanding

I will be keeping an eye out for other pages that I think would be good resources. If you have specific questions about SEO contact me, and I will try to add answers to them to future posts in this category (thanks!)


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How Does Google Look for Authoritative Search Results?

May 29, 2017 No Comments
A NASA Android that Voyaged to Space
A NASA Android that Voyaged to Space

If you’ve done any SEO for a site, you may recognize some of the steps involved in working towards making a website authoritative:

  1. Conduct keyword research to find appropriate terms and phrases for your industry and audience
  2. Review the use of keywords on the pages of your site to make sure it includes those in prominent places on those pages
  3. Map out pages on a site to place keywords in meaningful places
  4. The meaningful places on your pages are determined by information retrieval scores for HTML elements such as Titles and Headings and Lists
  5. The placement of keywords in prominent and important places on your pages can make your pages more relevant for those keywords
  6. Research the topics your pages are about, and make sure they answer questions that your audience may have about those topics in trustworthy and meaningful ways

Focus on Authoritative Search Results

A patent granted to Google this week focuses upon authoritative search results. It describes how Google might surface authoritative results for queries and for query revisions when there might not results that meet a threshold of authoritativeness for the initial query. Reading through it was like looking at a mirror image of the efforts I usually go through to try to build authoritative results for a search engine to surface. In addition to using some of the same language that I use to describe how I build authoritative pages, the patent also defines what an authoritative site is for us in terms that I might find myself using too:

In general, an authoritative site is a site that the search system has determined to include particularly trusted, accurate, or reliable content. The search system can distinguish authoritative sites from low-quality sites that include resources with shallow content or that frequently include spam advertisements. Whether the search system considers a site to be authoritative will typically be query-dependent. For example, the search system can consider the site for the Centers for Disease Control, “cdc.gov,” to be an authoritative site for the query “cdc mosquito stop bites,” but may not consider the same site to be authoritative for the query “restaurant recommendations”. A search result that identifies a resource on a site that is authoritative for the query may be referred to as an authoritative search result. The search system can determine whether to obtain an authoritative search result in response to a query in a variety of ways, which will be described below.

This definition seems to tell us that authoritative sites are high quality sites. The timing of a couple of other actions at Google seem to fit in well with the granting of this patent. Once is the publication of a Blog post by long time Google search engineer Ben Gomes (who joined Google in 1999), on steps they have taken to improve the quality of results at Google, titled Our latest quality improvements for Search. In that post, Ben points out that Google has published a brand new set of Search Quality Rater Guidelines – May 11, 2017, publicly, so that they are shared with the world instead of just to Google’s Search quality raters.

One of the named inventors on this patent was an inventor on another patent that I wrote about which focused upon high quality sites as well. That patent is worth reading about together with this one. That post is one I wrote named Google’s High Quality Sites Patent. As I said of that patent, it describes its purpose in this way:

This patent identifies pages that rank well for certain queries, and looks at the quality of those pages. If a threshold amount of those ranking pages are low quality pages, the search engine might use an alternative query to find a second set of search results that include pages from high quality sites. Those search results from the first query might then be merged with the results from the alternative query, with the pages from the low quality sites removed so that the search results include a greater percentage of pages from high quality sites.

So the aim of this new patent is to find results from higher quality search results. Google does seem to be targeting higher quality pages these days with the results they show.

Google sets a fairly high bar with search results, telling us in the description to this new patent:

Internet search engines aim to identify resources, e.g., web pages, images, text documents, multimedia content, e.g., videos, that are relevant to a user’s information needs and to present information about the resources in a manner that is most useful to the user.

In the summary section for this patent, the objective of the patent is identified to us as finding authoritative answers:

This specification describes how a system can improve search result sets by including at least one authoritative search result that identifies a resource on an authoritative site for a query. The system can include an authoritative search result, for example, when scores of an initial first search result set are low or when the query itself indicates that the user seeks resources from an authoritative site.

What this Patent Does

A search engine doesn’t choose the query terms that someone might use to perform a search with; but it might be able to identify query refinements based upon the initial query term. If the original query doesn’t return an authoritative result; Google might insert into the results shown for it some authoritative results for one of those query refinements based upon that original query. It might show that authoritative result at the top of the search results that it returns. This means that Google will be more likely to return high quality sites at the top of search results, rather than results from sites that might not be seen as authoritative sites.

The patent that was granted this week is:

Obtaining authoritative search results
Inventors: Trystan Upstill, Yungchun Wan, and Alexandre Kojoukhov
Assignee: Google Inc.
US Patent: 9,659,064
Granted: May 23, 2017
Filed: March 15, 2013

Abstract

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for obtaining authoritative search results. One of the methods includes receiving a first search query. First search results responsive to the first search query are obtained. Based on the first search query or the first search results, an authoritative search result that identifies a resource on a site that is authoritative for the first search query is obtained. A ranking of the authoritative search result and the one or more first search results is generated, and the ranking of the authoritative search result and the one or more first search results is provided in response to the first search query.

There were some really interesting points raised in the patent, which makes the whole thing worth spending time reading carefully:

1. Google might maintain a “keyword-to-authoritative site database” which it can refer to when someone performs a query.
2. The patent described “Mapping” keywords on pages on the Web as sources of information for that authoritative site database.
3. Google may also maintain “topic keyword and category keyword mappings to authoritative sites”.
4. Google may calculate confidence scores, which represent a likelihood that a keyword, if received in a query, refers to a specific authoritative site.
5. The patent talks about Mapping revised queries, like this: “The system can also analyze user query refinements to generate additional topic or category keyword mappings or refine existing ones.”
6. Interestingly, the patent talks about revisions in queries as being substitute terms that might be used “aggressively to generate revised search queries.” I’ve written about substitute terms before in How Google May Rewrite Your Search Terms.
7. If the original query, and the replacement query used to surface an authoritative result are similar enough (based upon a similarity score that would be used to compare them), that authoritative result may be demoted in the results shown to a searcher.


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New Finding Events Feature at Google Search

May 13, 2017 No Comments

This week Google rolled out an event finder on its mobile search app. You can read about it on:

Google Search will now help you find nearby events

The techcrunch article tells us that Google is working on suggestions for developers to have their events listed in search results – so we should be keeping an eye out for those as they get published.

I wrote about a patent here, in a post in November that talked about Ranking Events in Google Search Results, which focused upon a Google patent that had been granted August 23, 2016 titled Ranking events.

This feature is available in the United States starting today; but the Techcrunch article tells us that there are no plans for international expansion.

I tried a search for “sports events near me” on my phone this morning, and I did get the following result:

sports events near me

I’m wondering what events results look like in more urban areas. I did also search for music events:

Google Music Events Near Me

I suspect that this new feature might get a lot of use from people looking for something to do.

I like that it is including events from local schools and museums. It really looks useful.


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Will Google Start Giving People Social Media Influencer Scores?

April 29, 2017 No Comments

Social Media Influencer Scores

A patent granted to Google this week tells us about social media influencer scores developed at Google that sound very much like the scores at Klout. In the references section of the patent, Klout is referred to a couple of times as well, with a link to the Wikipedia Page about Klout, and the Klout FAQ page. We aren’t given a name for these influencer scores in Google’s patent, but it does talk about topic-based influencer scores and advertisers.

Many patents are published that might give the inventors behind those patents a right to the technology described in them, but often the decision to move ahead with the processes described in those patents might be based upon business-based matters, such as whether or not there might be value is pursuing the patent. When I read this patent, I was reminded of an earlier patent from Google from a couple of years ago that described an advertising model that used social media influencers and their interests called Adheat. That patent was AdHeat Advertisement Model for Social Network. A whitepaper that gives us a little more indepth information about that process was AdHeat: An Influence-based Diffusion Model for Propagating Hints to Match Ads. One of the authors/inventors, Edward Chang left Google after the paper came out to join HTC as their Vice President of Research and Innovation.

This new patent was originally filed on May 29, 2012. Edward Chang left Google for HTC in July, 2012. I don’t know if those events are related, but the idea of using social media influencers in advertising is an interesting one. The patent doesn’t pinpoint specific social media platforms that would be used the way that Klout does. Interestingly, Klout does use Google+ as one of the social media networks that they use to generate Klout Scores.

I like seeing what Google patents say about things on the Web. Their introduction to social media and to influencer scores was interesting:

Social media is pervasive in today’s society. Friends keep in contact throughout the day on social networks. Fans can follow their favorite celebrities and interact on blogs, micro-blogs, and the like. Such media are referred to as “social media,” which can be considered media primarily, but not exclusively, for social interaction, and which can use highly accessible and scalable communication techniques. Brands and products mentioned on such sites can reflect customers’ interests and feedback.

Some technologies have been developed to analyze social media. For example, some systems allow users to discover their “influence scores” on various social media. An influence score is a metric to measure a user’s impact in social media.

The patent tells us about the role of the process it defines:

…one aspect of the subject matter described in this specification can be embodied in methods that include the actions of identifying a user in a community; determining an influence score to be associated with the user in the community for a particular topic including determining a reach of one or more communications that relate to the particular topic that have been distributed from the user in the community; evaluating the reach as compared to one or more other users in the community for the particular topic; and storing the influence score in association with the user.

This new patent tells us about

  1. Identifying a user in a community;
  2. Determining an influence score to be associated with the user in the community for a particular topic,
  3. Determining a reach of communications that relate to the particular topic distributed from the user to other users in the community, and
  4. Evaluating that reach and comparing it to the reach of communications from other users in the community for the particular topic; and
  5. storing the influence score in association with the user.
  6. The patent also tells us that the following are advantages to be gained from the use of the process described in the patent:

    (1) The subject matter can be used to attribute viral growth to certain individuals or selected group.
    (2) Such attribution can be used for targeted advertising to the selected group or even to the individuals or other individuals that are influenced by the individual or group.

    The patent is:

    Determining influence in a social community
    Inventors: Emily K. Moxley, Vinod Anupam, Hobart Sze, Dani Suleman, Khanh B. Nguyen
    Assignee: Google Inc.
    US Patent 9,632,972
    Granted: April 25, 2017
    Filed: May 29, 2012

    Abstract

    Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining influence in a social community. In one aspect, a method includes identifying a user in a community; determining an influence score to be associated with the user in the community for a particular topic, including: determining a reach of one or more communications that relate to the particular topic that have been distributed from the user to other users in the community, and evaluating the reach as compared to the reach of one or more communications distributed from other users in the community for the particular topic; and storing the influence score in association with the user.

    The patent is worth reading in full, and it contains some interesting insights including some hints regarding whether Google might engage in this type of social media advertising (see the screenshot from the patent that starts this post, showing influencers and topic scores for them, which is described in a little more detail in the patent.

    I also liked this quote from the patent, and wanted to make sure that I shared it, because it raises a good point:

    Every community has individuals who influence that community. From a prominent economist’s advice on economics to a celebrity buying the latest designer bag, thousands of people pay attention to what influential individuals are doing within their field. However, less attention is paid when an influential individual opines on a topic outside their field. For example, the thousands of individuals that pay attention to the economists on economics would be unlikely to pay attention to the economist’s latest jacket purchase.

    These social media influencer scores do seem very similar to what Klout is doing. Would Google venture into such territory?


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Blackberry 8530 Smartphone Review

April 1, 2017 No Comments

With PDA s being restricted mostly to the business classes and
technocrats, RIM has launched the…
Cheap Phones


How Google May Rank Websites Based Upon Their Databases Answering Queries

March 30, 2017 No Comments

NASA Computer

Imagine that some sites might be ranked by Google based upon how their databases might answer queries. A patent from Google refers to this approach as one that looks at database service requirements to rank large sites such as sites that cover products, jobs, travel, recipes and movies. Such sites might include some static pages that provide examples of the capabilities of their databases, such as being able to provide answers to queries such as: “Brand X Cameras for less than $ 300.00”.

The patent provides some examples of the types of sites that are covered by this patent:

Many websites for which data available in resources store the data in large databases of structured information. For example, job search websites may have respective job databases, and respective resources (web pages) that include forms to search the databases. Likewise, recipe websites have respective databases for recipes, and movie websites have respective databases for movies. Requesting information for a certain recipe or movie causes the website to query its respective database and generate a webpage that presents the information in a structured format.

The patent tells us that most search engines do not account for the abilities of databases of such sites to respond to particular queries, which may make Google different from those search engines. The patent says:

However, many scoring algorithms do not score the search capabilities of a database when determining the relevance of a resource generated from data stored in the database. As a result, the search engine may not identify data that are particularly relevant to a query, and/or identify particular search capabilities that are available to the user that issued the query and that may help the user satisfy his or her informational need.

Imagine that Google may rank sites based upon “a service requirement score for the database.”

That service requirement score would be a measure of an ability of the database to fulfill the service requirement, which would enable it to respond to a query. I just wrote a post that described how Google is working to create a database of questions and answers to those, to show as “people also ask” questions, in the post: Google’s Related Questions Patent or ‘People Also Ask’ Questions. It’s not too much of a stretch to imagine that Google is saving up questions that might be asked about Jobs, Travel, commerce, movies, and recipes, and trying to determine which sites might be best at answering those questions, and ranking those sites on their ability to answer questions with different parameters, such as “a recipe for X that is under 1,000 calories.”

Advantages Under this Patent

The patent provides a couple of examples of advantages of using the processes described in this patent that are practical and helpful:

Websites need not generate multiple “optimized webpages” that are optimized for particular instances of queries to ensure that the website is identified in a search result. Instead, the underlying capabilities of the website database and the authority of the website are used as metrics to surface websites and databases that are of high quality with respect to a particular query. This reduces the overall cost of website management, and provides users with data that are more likely to satisfy the user’s informational need than the optimized webpages.

The systems and methods can utilize the conceptual schemas of the databases to provide additional information for queries that may not otherwise be derived from the queries. For example, a user that types in the search query [Brand X cameras under 300] may be searching for Brand X cameras that cost less than $ 300. The user, however, may not know that the “Q” models of Brand X cameras are prosumer models that each retail in excess of $ 300. Thus, by use of a product database, the search engine may determine that “Q” model are each in excess of $ 300. Thus, the search engine may modify the query with an operator that excludes the “Q” models, e.g., [Brand X cameras under 300 OP:NOT(Q)], or, alternatively, modify the query to emphasize resources that include reference to Brand X models that are priced under $ 300. The search engine thus surfaces fewer resources that include extraneous information, thereby satisfying the user’s informational need more quickly than if the extraneous information were provided.

The patent is:

Resource identification from organic and structured content
Inventors: Trystan G. Upstill and Jack W. Menzel
Assignee: Google Inc.
US Patent 9,589,028
Granted: March 7, 2017
Filed: March 16, 2016

Abstract

Methods, systems, and apparatus, including computer program products for structured content ranking. In an aspect, a method determines a service requirement from terms of a query, the service requirement being one of a plurality of service requirements fulfilled by databases; determines, for each of the databases, a service requirement score for the database, the service requirement score being a measure of an ability of the database to fulfill the service requirement; selects databases based on the service requirement scores; generates data responsive to the service requirement based on the terms of the query and one or more of the selected databases; and generates, from the data identifying resources that are determined to be responsive to the query and from the data responsive to the service requirement, search results that include first search results that each identify a corresponding resource that was determined to be responsive to the query.

SEO Based Upon Database Capabilities

This patent describes how sites might be ranked based upon their ability to answer questions from searchers instead of just how well optimized those sites might be based upon information retrieval relevance scores and link-based importance scores. We don’t know how much weight Google might give to a database service requirement ranking, but chances are, considering Google would be trying to find the most helpful sites, that may be considered an important metric. The detailed description for the patent starts off telling us this:

In some implementations, the search engine ranks results using a first ranking algorithm and based on non-semantic search terms, e.g., [nursing jobs]. The search system then accesses database information that describes the content and capabilities of website databases to determine which of the databases can fulfill a database service requirement. For example, if the query is [nursing jobs in Palo Alto over 100,000], the search system will identify jobs databases that have geographic and salary parameters that includes the values of “Palo Alto” and “100,000” or more. Using this information, the search engine may promote (or demote) search results referencing resources of a website that includes a database, and/or revise the query to include a constraint to filter out (or emphasize) resources that include certain terms.

The patent provides a definition of a service requirement:

a service that is requested, either implicitly or explicitly, by a query. For example, for the query [nursing jobs in Palo Alto over 100,000], the service requirement is a job search. Likewise, for the query [LAX to SFO] (or [Flights LAX to SFO]), the service requirement is a flight search.

Search Results Using Website’s Databases

The website databases may have different parameter types depending upon what kind of content is contained in the site. For instance:

…a flight search database may be configured to receive parameter values for the following parameter types: origin location, destination location, times and dates. Likewise, a job search database may be configured to receive parameter values for the following parameter types: location, job category, and salary.

These database parameters may be responded to by different parameter values, so

a particular job database may be tailored to only nursing jobs in New York and thus, the parameter value from the parameter type “Nursing Category” may be limited to specific nursing categories, e.g., Cardiology, Cardiothoracic, Hemodialysis, etc.

If Google is aware of the different parameters and values that respond to queries submitted to a site’s database, it can show those database results right in search results, as shown in this screenshot from the patent:

Database search results

I haven’t seen any search results quite like this yet, but it seems to be something to keep an eye open for.

Google may exclude some results from a query if they don’t fit what a person might have searched for as shown in this screenshot from the patent:

This makes search engines more like something that is searching a web sized database. This may be part of the future of SEO.


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