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How Google May Interpret Queries Based On Entity Information

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How Google May Interpret Queries Based On Entity Information


A new patent from Google dated December 28, 2021, focuses on how to interpret queries and solve them based on entity information.

I often link to Google patents in articles because I spend a lot of time learning from them.

Patents are filed to describe new inventions and spur innovation from potential competitors. They provide enough information to exclude others in the same business from copying the intellectual property of the patent filers.

Often, we find interesting information about assumptions that the creators of patents are making about search, searchers, and the Web that can make the patents an interesting read, as well.

As always, when I share the highlights in an article like this, you are encouraged to take a look at the patent itself.

I do try to explain what the patent may cover, but don’t want to cover it in so much detail that my post may seem to be a copy of the patent to indexing programs.

You may recall when Google search engineer Paul Haahr gave a presentation at SMX 2016 on “How Google Works.”

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One of the important takeaways was that Google tries to identify when entities are seen in queries submitted by searchers.

That statement leads to the question of how Google might be able to tell which entity might be referred to in a query.

Google has filed a patent where they explore that topic, and that is what this post is about.

How To Better Interpret Queries

Search has evolved to receive such search queries and return results responding to the query.

However, some search engines provide search results without understanding the search query.

For example, in response to [action movie with Tom Cruise], irrelevant search results like [Last Action Hero] and [Tom and Jerry] may be returned because a part of the search query gets included in the title of the pieces of content.

Understanding the search query can help the search engine produce more meaningful results.

How might a search engine interpret queries?

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The patent points out these methods:

  1. Receiving a query in a search domain.
  2. Deciding on search terms based on the query.
  3. Whether a search term corresponds to an entity name.
  4. Looking if the entity name is from metadata associated with the search domain.
  5. Seeing that many entity names correspond to at least a part of the number of search terms.
  6. Choosing an entity type and an entity score associated with each of the numbers of corresponding entity names.
  7. Finding a number of entity names by removing some matching entity names based on the entity score and contextual information in the received search query.
  8. Performing a search in the search domain with the remaining part of the number of entity names.
  9. Wherein each entity named in the remaining part of the number of entity names gets searched corresponding to the associated entity type.

This method to Interpret Queries can also include:

  • Receiving a voice query in a search domain.
  • Choosing, many voice recognition terms based on the received voice query.
  • Deciding on, for each of the numbers of voice recognition terms.
  • Whether at least a part of a voice recognition term corresponds to an entity name.
  • Wherein the entity name gets derived from metadata associated with the search domain and wherein an entity score gets associated with the entity name.
  • Determining a feasibility score for each of the number of voice recognition terms based on the entity score.
  • Ranking the number of voice recognition terms based on the determined feasibility score.
  • Selecting one of the numbers of ranked voice recognition terms for executing the voice query in the search domain.

This Query Interpretation patent is located at:

Methods, systems, and media for interpreting queries
Inventors: Yongsung Kim
Assignee: Google LLC
US Patent: 11,210,289
Granted: December 28, 2021
Filed: May 5, 2017

Abstract:

Mechanisms for interpreting queries to get provided.

In some implementations, a method for analyzing queries get provided, comprising:

Receiving a search query in a search domain

Determining search terms based on the search query

Determining, for each of the search terms, whether a search term corresponds to an entity name,

Wherein the entity name gets derived from metadata associated with the search domain.

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In response to determining that entity names correspond to a part of the search terms

Determining an entity type and an entity score associated with each of the corresponding entity names

Determining a remaining part of the entity names by removing at least one of the matching entity names based on the entity score and contextual information in the search query

Performing a search in the search domain with the remaining part of entity names,

Each entity named in the remaining part of entity names gets searched corresponding to the associated entity type.

The Interpret Queries Patent Conclusion

When a search engine identifies that an entity is in an article, it will try to identify specifically who the entity might be.

One Google patent I wrote about in the past explained that an entity name such as “Michael Jackson” might seem to identify just one person that most people would know. After all, he was a very well-known musician and entertainer.

But there was another well-known Michael Jackson who was nothing like that first; he was known as a Director of Homeland Security.

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Google does calculate confidence scores to determine which entity might be referred to when seen in a query.

This patent tells us about how Google might determine which entity is being searched for before returning results about that entity.

Keep in mind that when someone searches for “Lincoln” (an example from another Google patent) they could mean a lincoln town car, Former President Abraham Lincoln, or the City of Lincoln, Nebraska (also many other states).

If the search engine can interpret the query correctly, and show relevant answers to a searcher, they can satisfy the searcher’s informational or situational need.

There is a lot more analysis of how this patent works in the description of the patent, but I wanted to point out why it was needed and necessary.

There is too much risk of potential confusion if the search engine didn’t try to interpret a query correctly.

More resources:


Featured Image: Prabowo96/Shutterstock

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SEO

Link relevancy trumps volume for SEO

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Data speaks Link relevancy trumps volume for SEO

30-second summary:

  • Earned media coverage is more valuable than ever for your website
  • Digital PR is just as important as technical SEO
  • A large volume of links is the goal, what’s stopping someone from picking the most newsworthy idea, even if it has nothing to do with your client?

In 2022, it’s impossible to deny the benefit that digital PR as a tactic has on an organic growth strategy. Earned media coverage is more valuable than ever for your website. You could be doing everything right for SEO, but if you’re not building links, you’re still missing out on the increased search visibility, organic traffic, and brand awareness that backlinks bring to your business.

Last year, Google’s John Mueller finally weighed in on digital PR as a tactic and confirmed what we’ve all known for a while now: that it’s just as important — if not more — as technical SEO.

As digital PR is still a relatively “young industry” that’s only just sprouted up in the past 10 years, many PR pros have relied on “viral” campaigns to boost the backlink portfolio of their clients. These viral campaigns are often celebrated but are often created with little regard to how relevant, or “on-brand” those ideas really are.

After all, if a large volume of links is the goal, what’s stopping someone from picking the most newsworthy idea, even if it has nothing to do with your client?

In 2022, link volume is no longer the goal (or shouldn’t be)

While many PR pros’ were evaluating their success around this one key metric (link volume) others in the industry have suspected for a while now that the relevance of linking coverage is a key factor Google looks at when assigning “value” to links.

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Once again, John Mueller has settled the debate about link volume vs link relevance,  coming out in 2021 and saying that ‘the total number of links’ doesn’t matter at all.

This clarity has helped refocus the digital PR industry and forced PR pros to re-evaluate what metrics and KPIs we need to be focusing on to drive true organic growth.

It’s no longer enough to be ‘popular’ you also need to be relevant. Not just in terms of the publications you are targeting, but the keywords you want to rank for,  audience interest, and most importantly, brand alignment to the story you are pitching in.

Google is continuously looking to become more intelligent through its use of machine learning and artificial intelligence. It wants to understand web content as a human, and therefore through its use of natural language understanding, it is likely to not just be looking at the anchor text of links in third-party articles, but it is also wanting to understand the wider context of the article that a brand is placed in.

How to ensure your link-building activity is relevant to your brand

The first steps to coming up with relevant content ideas for your digital PR campaign are to:

  1.  understand your client, and
  2.  understand your client’s audience and their needs.

Every good idea will flow from these two pillars.

If Google’s main objective is to show the best content to users through search, then your job is to create content that either supports your client’s product or service or supports their customers.

It is more important than ever to not only create relevant and on-brand content in the written form but also ensure that any supporting assets created (video, images, audio) are also relevant to the target keywords and services or products that the brand sells.

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In addition, it’s important to create content that engages people, to drive further buzz and positive sentiment around the brand, all of which contribute to greater brand awareness and affinity among your potential customers.

How to measure the relevancy of your backlink profile

We now have the technology available to us to be able to understand and assign quantifiable metrics to the relevance of linking coverage (or indeed the relevance of any text-based content) – which allows us to be much more data-driven and targeted when developing digital PR, link creation activity and competitor and marketplace analysis.

For example, natural language understanding tools like Salient, measure the relevancy of both off-page and on-page content. Tools like this help to understand how a search engine is viewing a brand’s content, it not only enables us to identify the gaps in our client’s backlink profile.

At Journey Further, we use this proprietary tool to measure the relevancy of both off-page and on-page content for our clients.

Measuring the relevancy of your backlink profile

We can use this tool to understand how a search engine is viewing a brand’s content, it not only enables us to identify the gaps in our client’s backlink profile but also aids us in optimizing its content on-site. The outcome of which – is a much more focused, effective, and measurable digital PR activity that is better aligned to SEO objectives and that delivers better ROI for clients.

Looking ahead to 2023

Looking ahead to 2023 and beyond, it’s likely that Google will only continue to develop better technology to understand web content.

All digital PR campaigns should reflect this, and where possible, be multi-faceted, not just relying on a single press release to get cut through. We need to be thinking as marketers, not just SEO practitioners, and ensure we are driving as much ROI as possible. Taking a brand plus performance approach to SEO and digital PR will therefore be key.


Beth Nunnington is the VP of Digital PR and Content Marketing at Journey Further, leading Digital PR strategy for the world’s leading brands. Her work has been featured in The Drum, PR Moment, and Prolific North. Find Beth on Twitter @BethNunnington.

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