So I am trying to do a literature search, but am unsure of the name of the problem. I have a graph with edges weighted according to euclidean seperations of nodes (magnitudes only, no directional information). I am trying to convert this information into a n-dimensional space "embedding" (not sure this is what I should call it) of the graph. Such a representation will have nodes placed in space with seperation magnitudes the same as that of the graph edge weightings. Has anyone heard of anything like this?
I have an algorithm, but it only seems to work some on the time (but that may be due to rotten data)... Caveats: Please do ignore the unimportant degrees of freedom such as overall position, orientation, and inversion, these are not a great concern. Also, the multiple solutions of triangulation (circle intersections) may be ignored. I know there is no unique solution, but is my hope that I can massage an algorithm to give me the info I need. Also, ofcourse this is not in general possible to do. These graphs are somewhat special in that they form a space filling mesh of triangles. --~--~---------~--~----~------------~-------~--~----~ You received this message because you are subscribed to the Google Groups "Algorithm Geeks" group. To post to this group, send email to [email protected] To unsubscribe from this group, send email to [EMAIL PROTECTED] For more options, visit this group at http://groups.google.com/group/algogeeks -~----------~----~----~----~------~----~------~--~---
