I run a knowledge-sharing community where we try to make useful introductions between members of the community who would be the nodes. We are already able to score the quality of the match between members which we can translate into a weight for the edges between some of the nodes (we don't necessarily have edges between all nodes).
Every so often, I do a round of introductions. I could map these out in something like an affinity / adjacency matrix beforehand. I want each member to receive just one introduction so that the most in-demand members don't become inundated. So, I want to end up with optimised pairs of members to introduce to each other.
I'm trying to optimise the quality or value of introductions for the community as a whole which many mean that individual members are not introduced to their best match if that means the overall "score" for the group matches / introductions is higher.
Any ideas about how I could achieve this very gratefully received! Thanks, JPStatistics:Posted by jpdoggett — 03 Nov 2017 13:22
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