Modifications

I am back from the holiday season and looking at the current state of the output file...

It doesn't take much of a dataset file to overwhelm the code, and or create an unhelpfully obfuscated network of connection lines. I believe that the code can still be viable if I make a few alterations to how deep the linkage tree for each query will go. The thinking is, at six degrees of Kevin Bacon we are no longer developing fruitful hybrid concepts to solve our quandaries, so lets limit the number of degrees we look through.

So in an attempt to fix these problems, I am going to replace the random positions of concepts with a directional branching system generated from the sequential discovery of concept terms as the query trees are walked out by the code.

I was realizing that the position of a concept in the output display does not need to be known until it is displayed. This affords me the ability to increment the position of the x axis during each degree of the query tree. This will produce a stepped visual breakdown of the position of the concepts included in the queries based on how many degrees of separation they have from the original primary concept query.
I will use this leveled visual output formation along with a limited number of possible degrees of separation, and provide visualization of links to all of the primary concepts any subject compliment in either data tree is linked to regardless of weather or not that subject compliment is shared between the two query trees.

In this way the two sets of dependant attribute subject compliment trees will reveal all of their parent concepts and the dataset visualization will not fall prey to showing lots of peripherally associated concepts. But it will now give us a lead to the concepts that contain as attributes the concepts that are connected to the two query trees.