What would be the best way to both segregate and filter shapes.
As an example: We have shapes ( circle, triangle, square ) with different colors and sizes.
We want to:
First - Segregate them by shape, color or size or a combination of them (size,color), (shape, color) ,etc.
So we get one node per segragated group with a value indicating how many are part of this group.
Second - Filter the yellow only or the blue and big ones or circle etc.
So the value in the node for each group represent this segregation and filtering
In the real problem that I have, there are up to 10 cathegories and up to 5000 values for each of these cathegories. One or two cathegories might have up to 100 000 values.
An other level to this problem, it's to have a count of persons who like a node ( group as described above ) knowning that a person can like multiple group
Anyway, this is a big problem regarding much more than shapes in many industries
Could you draw an example with https://arrows.app, I tried this approach once and it was qualified as a naive approach but in the end didn't work as expected with large data.
I don't get what's the role of your objects in your example if you create one node for each shape, color, etc.