The simple how it works

These images are a description that some people have been asking me to provide to clarify the way Pointsware works.
This example illustrates the process Pointsware uses to collapse separate descriptive textual spaces onto one another to reveal linkages between ideas.

Here is the dataset used:

apple,red,fruit,tree
tree,grows,wood,green,leaves,roots,life
child,baby,grows,birth,cry,fear

The dataset above is a simplified version to show the comma delimited format and can be cut and pasted into the dataset window of the Pointsware interface and with queries apple and child used to make a sample SVG file for testing.

Larger files working much better!

The larger files are working much better now that the degrees are limited and the server processor is keeping up with demand!! Please feel free to give the new code a try and let me know what you think.

The next thing to do is work on the documentation, instructions and put some examples up on the site of the datasets and outputs so it is clearer how I have been using this tool.

Degrees of seperation now limited

The subject compliment linkage paths which were being extended as far out into the dataset as there were connections to be found have now been limited to three levels of separation. This should make for simpler and more readable output display images. The load on the server side computer is also now seemingly under control. I still have to whip up a large complicated dataset file and test the speed of the data analysis but here is to having your fingers crossed.
also I have changed the nodework morphology from a cloud presentation to a tree that extends in levels from the left side of the display image. The tree will help illustrate the levels of separation from the query terms.