# Clustering based on interactions between members of two groups

I have a large dataset from a survey that describes what web pages people use. So for each person I have a list of pages that they visit and how frequently they visit them. What methods can be used to cluster both the webpages (based on similar users who use them) and the users (who use similar webpages).

Example>
User A visited web pages a, b, a, c
User B visited a, b, d, b
User C visited page e, e


Conclusion from that would be that pages a,b,c,d are somewhat similar and belong to the same cluster. The other cluster is page e. Also, users a,b are similar, the other user cluster is the one containing User C, who visits different pages.

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