Automatic Knowledge Construction

Information filtration and merge alone are very powerful features. However, the combination of the filtration and merge has a synergistic effect where you merge multiple diagrams into one and at the same time apply information filtration. We call this feature automatic knowledge construction. Imagine the situation where a scientist reads an article about how subject A relates to the subject C. However, he does not care about subject C, he wants to know how the subject A relates to the subject D. With our technology a scientist can automatically switch the context from subject C to subject D.

Figure illustrates the principle of automatic knowledge construction

The principle of an Automatic Knowledge Construction. The first step is to merge Diagram1 and Diagram2 that have information that needs to be connected (C and D elements respectively). The second step is to filter out information that is not necessary (A element). By comparing the Final Diagram with Diagram1, we can clearly see that the context has been changed. Now D instead of A has a non-direct connection to C. Green elements represents scientific statements. Lines that connect these elements indicate relations between the statements.