Utilize the course transcript as an exhaustive foundational resource to systematically develop a sophisticated set of prompts that strategically leverage the material for creating an advanced, AI-driven Semantic SEO Article Writer. Begin by thoroughly brainstorming to meticulously identify and define the optimal AI agents essential for this task, emphasizing their semantic expertise and specific roles in the content creation process. For each agent, construct a lexicon-optimized role description that maximizes their proficiency in crafting semantically rich SEO content.

Subsequently, generate a comprehensive suite of meticulously crafted, semantically enriched prompts for each agent, precisely optimized to harness GPT-4's advanced capabilities to their fullest extent. These prompts should be tailored to each agent's specialized function, ensuring they effectively utilize the course material to produce high-quality, semantically optimized SEO articles. This approach is designed to maximize the efficacy of the AI-driven writer, delivering content with unparalleled depth, clarity, coherence, and persuasive impact.
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Hello In this lecture we will talk about the user behaviors and the query semantics First query semantics come from user behaviors and user perception They don't come from dictionaries And it means that every word or every search term they take their relevance and their meaning from the users behaviors and users perception That's why despite German and Lithuania are not that much close to each other thanks to users they suddenly become actually similar or relevant And in this case we will talk about clustering A search engine can cluster only three things documents queries and users A search engine's purpose is basically matching queries to topics and entities and topics and entities to the documents and documents to the users so that user can reach out to the document via topics contents and the queries But in this case sometimes a few complicated things might happen Here we have three queries and three users Let's assume that user one only searches for only searches for the query one and query two Then we see that user three searches for query three and the query two We see that user two that person searches for query one and the query three but the person doesn't search for the query two in this case So there are a few concepts here that you will need to understand One is correlating queries query path and sequential queries So basically query path is which query has been searched after what query If query one has been searched first then the query three it means that query path goes like query one and query three If it is search if the person searches first the let's say the query two then the query one it goes two to the one The second thing is correlating queries Which query has been searched together with another which another And in this case we see that actually none of these three queries are being searched together Only two of them always are being searched together Which means that there is not an absolute correlation between them Then we see the sequential queries Sequential query is about actually a kinds of search session Let's say this line here it represents a search session and this line here it represents another search session In this case you can see that the query three maybe appears in this part and query one appears in this part If search engine decides that both of these query sessions appear from the same search context or the users state they don't take this middle grounds and they directly assume that these two queries are actually coming from the same search state That's why they directly relate these two queries to each other But the thing here is that how we can create a query cluster because none of these none of these three things are being actually searched at the same time If you accept that these three users are actually the same user and you will realize that the same user actually are searching all these three queries at the same time The real magic happens actually where you put the border because if you take these two users then the query paths and the correlations and the sequential queries they all will be changing If you take it like this again everything will be changing one more time If you take it like all these three then it's easier but this time you can realize that some of the really small websites small sources they might lose traffic or some of the affiliate sources suddenly their topical coverage might be decreased too Because if you are targeting these users here actually their behaviors and their entities that appear inside these queries and the query context all these things actually will be determining your borders That's why in our topical maps usually we try to go broader so that we can always stay safe even if everything goes wrong One more thing that you should keep in your mind I won't talk about the the theories that much in the future lectures is actually semantic distance In every core algorithm update the semantic distance between the topics it changes That's why in the previous lecture we talked about content and the relevance configuration and it's done always on process And that's why in our content briefs we never leave gap We cover everything without any kinds of luck We determine everything nothing is random everything is planned and we cover everything in the best possible details and a highly accurate way So that search engine can't find any chance besides ranking us Thank you In the next lecture we will see topical map of this project 
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