How does the [[backlink]] syntax work in InfraNodus and what's its difference from LogSeq / Obsidian?

InfraNodus uses the [[back link]] or [[wikilink]] syntax to identify the phrases and entities that should be processed as separate nodes in the network graph and linked together.

It is also used in a similar way in personal knowledge management tools like Obsidian, LogSeq or Roam Research to link ideas together. 

However, there is a difference.

Let's say you have a document called "Network Science" in Obsidian / LogSeq which contains the following sentence:

[[Betweenness centrality]] is a measure of [[influence]]. It is used to understand which [[nodes]] appear most often on the [[shortest path]] between any two randomly chosen nodes in a network.

Both of these tools will build the following graph as a result:

The "host" page [[network science]] is connected to all the other [[backlinks]] mentioned on that page.

However, those pages are not connected to each other. 

This is a problem, because, in fact, we're using [[betweenness centrality]] in the same context as the [[shortest path]]. Roam Research is the only software that takes account of that by providing the information about the backlinks, but it still doesn't show this in a graph.

That's why in InfraNodus we treat these connections slightly differently. We do not only connect the concepts that appear inside a page to that page, but also all the [[backlinks]] that are mentioned in the same context, following the 4-gram logic (a window scan that contains 4 words at a time). So, as a result, you get this graph: 

As you can see, the concepts that are used in the same context, are connected to one another, as well as to the page where they are mentioned. 

This provides a much more precise representation of how the different ideas are connected.

You can also switch the 4-gram connection to 2-gram connections (so only the concepts that directly follow each other are connected) in the Global Settings of InfraNodus.