LSI (Latent Semantic Indexing) for relevance

[fomayof928@mowline]

Summaries are also hidden gems. We see Google looking for content summaries all the time. They’re providing summaries in featured snippets and various SERP features to help users distill information. So if you can do that, not only will you make your content easier to scan, but you’re also making it more accessible for search, which is great.

☑ TF-IDF (Term Frequency-Inverse Document Frequency)
TF-IDF stands for “Term Frequency-Inverse Document Frequency.” It sounds a little scary. It’s actually pretty simple. How many times is “chakra stones” mentioned on that particular page divided by argentina number data number of times it’s mentioned anywhere else? It’s basically just a calculation to determine the relevance of the term “chakra stones.” Really cool and commonly used by Google. So if you can do this on your page, it’ll help you in the long run.


Similarly, LSI or LSA, as it is sometimes referred to, is latent semantic indexing, and it's also for relevance. It helps determine, well, if I'm talking about chakra stones, it might also include other topics that are generally related to that topic. Related

☑ Flesch-Kincaid Reading Proficiency Test
What is the readability of this page? The easier it is to read, the better, but you just want to keep an eye on it in general.