Internal linking : Standard linking vs Neural SEO Network linking

standard vs neural seo linking

What is internal linking ?

Internal links are the hyperlinks from one page to another within same domain, usually helping search engines bots and users to understand the website structure and easy navigation from one page to another.

Standard vs Neural Network

Most websites follow a top down / tree approach of internal linking. Some have cross linking from one page to another for conversions while some have too many categories which makes it hard to link from one another.

The primary usage of internal linking is to navigate between the pages. Search engine’s user agents(bots) use internal linking to know more about the website structure and also to study which category the pages fall into. From a user’s point of view internal linking serves the purpose of helping with better navigation within a website. For example, a user that is looking specifically to buy a TV can get to the “electronics” tab and from there find the exact product that the user is looking for. This improves the user’s experience and also ease in getting to the product without having to go through a ton of pages to get to what is needed.

Strong connections within a website will let the SEO link juice to pass which in turn improves the page’s ranking in the search engine. Typically, the standard approach to linking the pages of a website uses a top down model. This model has the drawback of having gaps within the linking when it comes to the nodes that are at the end of the tree. Also having orphan pages that are not linked properly will result in the pages not having an index within the search engine and this will also further reduce the ranking of the website on the whole. Using a top down approach when it comes to managing millions of pages, puts the product owner at a disadvantage.

Neural SEO network’s patented linking algorithm links up pages belonging to different categories without leaving out orphan pages. The connectivity is greatly improved between the pages. Also better link equity is passed with neural networks.

Search engines use neural mapping algorithms for understanding a website. This AI technology understands languages and search terms leading to better latent semantic index. For example a search for electronics on a search engine displays TVs, laptops, cameras etc.,. And further searches looking for a TV will bring out pages that show TVs from different brands. This display of results on the search engine’s results page(SERP) is due to the indepth and granular understanding of keyword mapping in the search engine. Also the word “Central” in America is the same as “Sentral” in Malaysia. Although the words are of different languages, they still have the same meaning. This understanding of the languages also helps in bringing out appropriate results on SERP.

Neural SEO network’s patented AI algorithm understands the language and semantic indexes resulting in better mapping leveraging Word2Vec model too. Also this linking algorithm provides better indexation of your pages and ranking within the search engine results pages.