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Counting Simplices in Hypergraph Streams

Published 21 Dec 2021 in cs.DS | (2112.11016v1)

Abstract: We consider the problem of space-efficiently estimating the number of simplices in a hypergraph stream. This is the most natural hypergraph generalization of the highly-studied problem of estimating the number of triangles in a graph stream. Our input is a kk-uniform hypergraph HH with nn vertices and mm hyperedges. A kk-simplex in HH is a subhypergraph on k+1k+1 vertices XX such that all k+1k+1 possible hyperedges among XX exist in HH. The goal is to process a stream of hyperedges of HH and compute a good estimate of Tk(H)T_k(H), the number of kk-simplices in HH. We design a suite of algorithms for this problem. Under a promise that Tk(H)TT_k(H) \ge T, our algorithms use at most four passes and together imply a space bound of O(ϵ<sup>2</sup>logδ<sup>1</sup>polylognminm<sup>1+1/k/T,</sup>m/T<sup>2/(k+1)</sup>)O( \epsilon<sup>{-2}</sup> \log\delta<sup>{-1}</sup> \text{polylog} n \cdot \min{ m<sup>{1+1/k}/T,</sup> m/T<sup>{2/(k+1)}</sup> } ) for each fixed k3k \ge 3, in order to guarantee an estimate within (1±ϵ)Tk(H)(1\pm\epsilon)T_k(H) with probability at least 1δ1-\delta. We also give a simpler $1$-pass algorithm that achieves O(ϵ<sup>2</sup>logδ<sup>1</sup>logn(m/T)(ΔE+ΔV<sup>11/k</sup>))O(\epsilon<sup>{-2}</sup> \log\delta<sup>{-1}</sup> \log n\cdot (m/T) ( \Delta_E + \Delta_V<sup>{1-1/k}</sup> )) space, where ΔE\Delta_E (respectively, ΔV\Delta_V) denotes the maximum number of kk-simplices that share a hyperedge (respectively, a vertex). We complement these algorithmic results with space lower bounds of the form Ω(ϵ<sup>2)\Omega(\epsilon<sup>{-2}), Ω(m<sup>1+1/k/T)\Omega(m<sup>{1+1/k}/T), Ω(m/T<sup>11/k)\Omega(m/T<sup>{1-1/k}) and Ω(mΔV<sup>1/k/T)\Omega(m\Delta_V<sup>{1/k}/T) for multi-pass algorithms and Ω(mΔE/T)\Omega(m\Delta_E/T) for $1$-pass algorithms, which show that some of the dependencies on parameters in our upper bounds are nearly tight. Our techniques extend and generalize several different ideas previously developed for triangle counting in graphs, using appropriate innovations to handle the more complicated combinatorics of hypergraphs.

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