GOOGLE

Google BERT Update – What it Means

Published

5 years ago

October 25, 2019

google bert update what it means via martinibuster

Google announced what they called the most important update in five years. The BERT update impacts 10% of search queries. What is BERT and how will it impact SEO?

BERT is a Major Google Update

According to Google this update will affect complicated search queries that depend on context.

This is what Google said:

“These improvements are oriented around improving language understanding, particularly for more natural language/conversational queries, as BERT is able to help Search better understand the nuance and context of words in Searches and better match those queries with helpful results.

Particularly for longer, more conversational queries, or searches where prepositions like “for” and “to” matter a lot to the meaning, Search will be able to understand the context of the words in your query. You can search in a way that feels natural for you.”

What is the BERT Algorithm?

Search algorithm patent expert Bill Slawski (@bill_slawski of @GoFishDigital) described BERT like this:

“Bert is a natural language processing pre-training approach that can be used on a large body of text. It handles tasks such as entity recognition, part of speech tagging, and question-answering among other natural language processes. Bert helps Google understand natural language text from the Web.

Google has open sourced this technology, and others have created variations of BERT.”

The BERT algorithm (Bidirectional Encoder Representations from Transformers) is a deep learning algorithm related to natural language processing. It helps a machine to understand what words in a sentence mean, but with all the nuances of context.

BERT And On Page SEO

I asked search algorithm expert Dawn Anderson (@dawnieando on Twitter) what that meant for SEOs and she responded that it won’t help websites that are poorly written.

According to Dawn:

“BERT and family improve the state of the art on 11 natural language processing tasks. Even beating human understanding since linguists will argue for hours over the part of speech a single word is.

But what if the focus of a page is very weak? Even humans sometimes will be like “what’s your point?” when we hear something.

And pronouns have been very problematic historically but BERT helps with this quite a bit. Context is improved because of the bi-directional nature of BERT.

There will still be lots of work for us to do since we need to emphasise importance, utilise clear structures, help to turn unstructured data into semi structured data, utilise cues on content light pages (e.g. image heavy but not text heavy eCommerce pages) using such things as internal linking.”

BERT Improves Search Query Understanding

Google’s BERT Update improves how Google understands search queries. BERT analyzes search queries, not web pages. However, as Dawn said, on page SEO becomes more important in terms of using words in precise ways. Sloppy content may not be helped by the Google BERT update.

Dawn Anderson observed:

“It’s knocking human understanding out of the water in loads of natural language understanding tasks. BERT is like a WordPress plugin which is a starting point and then they customise it and improve it.

The word “rose” means several things but it’s exactly the same word. The context must accompany the word otherwise the word means nothing.”

Dawn is correct. During the course of researching a presentation I was to give at PubCon Vegas 2019, I did a search for a tricky phrase that relied on context to get it right.

An Example of Context and BERT

The phrase was “how to catch a cow fishing?”

In New England, the word “cow” in the context of fishing means a large striped bass.

A striped bass is a popular saltwater game fish that millions of anglers fish for on the Atlantic coast.

So I typed the phrase, “how to catch a cow fishing” and Google provided results related to livestock, to cows.

Even though I had purposely used the word “fishing” to provide context, Google ignored that context and provided results related to cows. That was on October 1, 2019.

Today, October 25, 2019 the same query results in search results that are full of striped bass and fishing related results.

The BERT algorithm appeared to have understood the context of the word “fishing” as important and changed the search results to focus on fishing related web pages.

Dawn Anderson explained that new search result like this:

“Bass means different things. There are different meanings for the single words. The context around the word provides more meaning.”

She’s right. That’s exactly what Google did in the search query, “how to catch a cow fishing.” BERT appears to have used the word “fishing” to add context to that search query.

BERT May Be Just the Beginning

Dawn Anderson said:

“A researcher I know used BERT in his work with assistants, e.g. similar to Google Assistant, to test the use of clarifying questions. So it has many uses. It’s just a starting point.”

I asked:

“So you see this as one step in a longer journey?”

And Dawn replied:

“Yes, but it’s a big step. Huge… It’s like a quantum leap huge.”

I agree. I wouldn’t go out and create thousands of longtail phrases to try to capitalize on Google’s ability to understand context better.

However, like Dawn, I see this as an opportunity to bring more traffic with content that is more focused and well organized.

Searchenginejournal.com

GOOGLE

Google Warns About Misuse of Its Indexing API

Published

3 weeks ago

September 12, 2024

Max

Google Warns About Misuse of Its Indexing API

Google has updated its Indexing API documentation with a clear warning about spam detection and the possible consequences of misuse.

Warning Against API Misuse The new message in the guide says:

“All submissions through the Indexing API are checked for spam. Any misuse, like using multiple accounts or going over the usage limits, could lead to access being taken away.”

This warning is aimed at people trying to abuse the system by exceeding the API’s limits or breaking Google’s rules.

What Is the Indexing API? The Indexing API allows websites to tell Google when job posting or livestream video pages are added or removed. It helps websites with fast-changing content get their pages crawled and indexed quickly.

But it seems some users have been trying to abuse this by using multiple accounts to get more access.

Impact of the Update Google is now closely watching how people use the Indexing API. If someone breaks the rules, they might lose access to the tool, which could make it harder for them to keep their search results updated for time-sensitive content.

How To Stay Compliant To use the Indexing API properly, follow these rules:

Don’t go over the usage limits, and if you need more, ask Google instead of using multiple accounts.
Use the API only for job postings or livestream videos, and make sure your data is correct.
Follow all of Google’s API guidelines and spam policies.
Use sitemaps along with the API, not as a replacement.

Remember, the Indexing API isn’t a shortcut to faster indexing. Follow the rules to keep your access.

GOOGLE

This Week in Search News: Simple and Easy-to-Read Update

Published

3 months ago

June 30, 2024

Entireweb News Bot

This Week in Search News: Simple and Easy-to-Read Update

Here’s what happened in the world of Google and search engines this week:

1. Google’s June 2024 Spam Update

Google finished rolling out its June 2024 spam update over a period of seven days. This update aims to reduce spammy content in search results.

2. Changes to Google Search Interface

Google has removed the continuous scroll feature for search results. Instead, it’s back to the old system of pages.

3. New Features and Tests

Link Cards: Google is testing link cards at the top of AI-generated overviews.
Health Overviews: There are more AI-generated health overviews showing up in search results.
Local Panels: Google is testing AI overviews in local information panels.

4. Search Rankings and Quality

Improving Rankings: Google said it can improve its search ranking system but will only do so on a large scale.
Measuring Quality: Google’s Elizabeth Tucker shared how they measure search quality.

5. Advice for Content Creators

Brand Names in Reviews: Google advises not to avoid mentioning brand names in review content.
Fixing 404 Pages: Google explained when it’s important to fix 404 error pages.

6. New Search Features in Google Chrome

Google Chrome for mobile devices has added several new search features to enhance user experience.

7. New Tests and Features in Google Search

Credit Card Widget: Google is testing a new widget for credit card information in search results.
Sliding Search Results: When making a new search query, the results might slide to the right.

8. Bing’s New Feature

Bing is now using AI to write “People Also Ask” questions in search results.

9. Local Search Ranking Factors

Menu items and popular times might be factors that influence local search rankings on Google.

10. Google Ads Updates

Query Matching and Brand Controls: Google Ads updated its query matching and brand controls, and advertisers are happy with these changes.
Lead Credits: Google will automate lead credits for Local Service Ads. Google says this is a good change, but some advertisers are worried.
tROAS Insights Box: Google Ads is testing a new insights box for tROAS (Target Return on Ad Spend) in Performance Max and Standard Shopping campaigns.
WordPress Tag Code: There is a new conversion code for Google Ads on WordPress sites.

These updates highlight how Google and other search engines are continuously evolving to improve user experience and provide better advertising tools.

AI

Exploring the Evolution of Language Translation: A Comparative Analysis of AI Chatbots and Google Translate

Published

7 months ago

February 26, 2024

Max

A Comparative Analysis of AI Chatbots and Google Translate

According to an article on PCMag, while Google Translate makes translating sentences into over 100 languages easy, regular users acknowledge that there’s still room for improvement.

In theory, large language models (LLMs) such as ChatGPT are expected to bring about a new era in language translation. These models consume vast amounts of text-based training data and real-time feedback from users worldwide, enabling them to quickly learn to generate coherent, human-like sentences in a wide range of languages.

However, despite the anticipation that ChatGPT would revolutionize translation, previous experiences have shown that such expectations are often inaccurate, posing challenges for translation accuracy. To put these claims to the test, PCMag conducted a blind test, asking fluent speakers of eight non-English languages to evaluate the translation results from various AI services.

The test compared ChatGPT (both the free and paid versions) to Google Translate, as well as to other competing chatbots such as Microsoft Copilot and Google Gemini. The evaluation involved comparing the translation quality for two test paragraphs across different languages, including Polish, French, Korean, Spanish, Arabic, Tagalog, and Amharic.

In the first test conducted in June 2023, participants consistently favored AI chatbots over Google Translate. ChatGPT, Google Bard (now Gemini), and Microsoft Bing outperformed Google Translate, with ChatGPT receiving the highest praise. ChatGPT demonstrated superior performance in converting colloquialisms, while Google Translate often provided literal translations that lacked cultural nuance.

For instance, ChatGPT accurately translated colloquial expressions like “blow off steam,” whereas Google Translate produced more literal translations that failed to resonate across cultures. Participants appreciated ChatGPT’s ability to maintain consistent levels of formality and its consideration of gender options in translations.

The success of AI chatbots like ChatGPT can be attributed to reinforcement learning with human feedback (RLHF), which allows these models to learn from human preferences and produce culturally appropriate translations, particularly for non-native speakers. However, it’s essential to note that while AI chatbots outperformed Google Translate, they still had limitations and occasional inaccuracies.

In a subsequent test, PCMag evaluated different versions of ChatGPT, including the free and paid versions, as well as language-specific AI agents from OpenAI’s GPTStore. The paid version of ChatGPT, known as ChatGPT Plus, consistently delivered the best translations across various languages. However, Google Translate also showed improvement, performing surprisingly well compared to previous tests.

Overall, while ChatGPT Plus emerged as the preferred choice for translation, Google Translate demonstrated notable improvement, challenging the notion that AI chatbots are always superior to traditional translation tools.

Source: https://www.pcmag.com/articles/google-translate-vs-chatgpt-which-is-the-best-language-translator