I have a data set that is similar to this:
- 10,000 jobs with 200,000 applicants which are linked to a job.
I'm looking to cluster the shared jobs based on applicants that they share, am I reinventing the wheel looking to build this or is there a common solution?
Most of the example I found all require a "distance" but I can't see how I could compute one in this case?
Edit: To add, the clustering criteria would be fairly straightforward more than X applicants (say 5) in common, with only a single cluster per job.