When the acorn that would become the SEO industry started to grow, indexing and ranking at search engines were both based purely on keywords.
The search engine would match keywords in a query to keywords in its index parallel to keywords that appeared on a webpage.
Pages with the highest relevancy score would be ranked in order using one of the three most popular retrieval techniques:
- Boolean Model
- Probabilistic Model
- Vector Space Model
The vector space model became the most relevant for search engines.
I’m going to revisit the basic and somewhat simple explanation of the classic model I used back in the day in this article (because it is still relevant in the search engine mix).
Along the way, we’ll dispel a myth or two – such as the notion of “keyword density” of a webpage. Let’s put that one to bed once and for all.
The keyword: One of the most commonly used words in information science; to marketers – a shrouded mystery
“What’s a keyword?”
You have no idea how many times I heard that question when the SEO industry was emerging. And after I’d given a nutshell of an explanation, the follow-up question would be: “So, what are my keywords, Mike?”
Honestly, it was quite difficult trying to explain to marketers that specific keywords used in a query were what triggered corresponding webpages in search engine results.
And yes, that would almost certainly raise another question: “What’s a query, Mike?”
Today, terms like keyword, query, index, ranking and all the rest are...
Read Full Story: https://searchengineland.com/indexing-keyword-ranking-techniques-history-386936
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