Clustering in Hypergraphs to Minimize Average Edge Service Time

Ori Rottenstreich, Haim Kaplan, Avinatan Hassidim

Research output: Contribution to journalArticlepeer-review


We study the problem of clustering the vertices of a weighted hypergraph such that on average the vertices of each edge can be covered by a small number of clusters. This problem has many applications, such as for designing medical tests, clustering files on disk servers, and placing network services on servers. The edges of the hypergraph model groups of items that are likely to be needed together, and the optimization criteria that we use can be interpreted as the average delay (or cost) to serve the items of a typical edge. We describe and analyze algorithms for this problem for the case in which the clusters have to be disjoint and for the case where clusters can overlap. The analysis is often subtle and reveals interesting structure and invariants that one can utilize.

Original languageEnglish
Article number40
JournalACM Transactions on Algorithms
Issue number3
StatePublished - Jun 2020


  • Clustering
  • average cover time
  • hypergraphs
  • set cover


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