What the QBST is and how it functions (Part 1).

Recently I read a discussion about QBST from the esteemed Shaun Anderson. The article defines QBST (Query-Based Salient Terms) as a fundamental Google algorithm that works as a «memorization system». For a particular search query, QBST «memorizes» a list of words, phrases and concepts that it expects to find on a relevant page. For example, for «best running shoes» it expects to see the words «cushioning», «stability», «lightweight», etc.

The author claims that this discovery confirms long-standing theories in SEO about co-occurring words (co-occurring words) and topical authority (topical authority). The basic strategy for implementation is reverse engineering. You need to analyze the top pages to identify these «meaningful terms» and create comprehensive content that naturally incorporates this constellation of words.

Checked all these assertions in the Memorandum Opinion I mentioned earlier on the text of the judicial opinion.

So, the article is absolutely right that the concept of a «memory system» was central to the witnesses' testimony. However, the Judge's final Memorandum Opinion attributes this function primarily to the Navboost system, not the QBST.

Quoting from the document (Page 157):
«Navboost is a “memorization system” that aggregates click-and-query data about the web results delivered to the SERP. Liab. Tr. at 1804:8-1805:22, 1806:8-15 (Lehman). Like Glue, it can be thought of as “just a giant table.” Id. at 1805:6-13 (Lehman).»

This is a key point. The judge in his final decision singles out Navboost specifically as a system that «remembers» successful user interactions. It works like a giant spreadsheet, linking queries to URLs where users have completed their search (long click). The article cites an earlier document from the case («Plaintiffs’ Proposed Findings of Fact») where the witness's testimony may have been presented differently. The judge's final ruling, however, focuses on Navboost as the primary «memory system» based on user behavior.

When searching the entire text of the Memorandum Opinion, the terms «QBST» and «Query-Based Salient Terms» do not appear once.

This does not mean that such a system does not exist or that the witness did not mention it. It means that in his final, summary decision, the judge found the Navboost/Glue (click-based) and RankEmbed (AI model for understanding semantics) systems to be more important and fundamental to the case. It is likely that QBST is either part of these systems or an older/supplementary algorithm that was not singled out as a key factor in dominance.

Shaun Anderson's article is correct at its core: Google has a mechanism that determines the thematic relevance of a page based on the presence of expected terms and concepts on the page. However, according to the final court document, the main «memorization system» is Navboost, which remembers successful behavioral cues, not just a set of words. QBST is likely a mechanism that analyzes content to predict which page is most likely to trigger those successful behavioral cues.

Thus, you should not believe everything that is said, even by the most authoritative comrades (I can). Especially do not believe John Mueller )))) You should always check the data and facts.

Next, I'll talk about the practical use of this system to improve rankings.