human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "log diameter rounds algorithms for 2 vertex and 2 edge connectivity"):
  Abstract: Many modern parallel systems, such as MapReduce, Hadoop and Spark, can be modeled well by the MPC model. The MPC model captures well coarse-grained computation on large data --- data is distributed to processors, each of which has a sublinear (in the input data) amount of memory and we alternate between rounds of computation and rounds of communication, where each machine can communicate an amount of data as large as the size of its memory. This model is stronger than the classical PRAM model, and it is an intriguing question to design algorithms whose running time is smaller than in the PRAM model. #R##N#In this paper, we study two fundamental problems, $2$-edge connectivity and $2$-vertex connectivity (biconnectivity). PRAM algorithms which run in $O(\log n)$ time have been known for many years. We give algorithms using roughly log diameter rounds in the MPC model. Our main results are, for an $n$-vertex, $m$-edge graph of diameter $D$ and bi-diameter $D'$, 1) a $O(\log D\log\log_{m/n} n)$ parallel time $2$-edge connectivity algorithm, 2) a $O(\log D\log^2\log_{m/n}n+\log D'\log\log_{m/n}n)$ parallel time biconnectivity algorithm, where the bi-diameter $D'$ is the largest cycle length over all the vertex pairs in the same biconnected component. Our results are fully scalable, meaning that the memory per processor can be $O(n^{\delta})$ for arbitrary constant $\delta>0$, and the total memory used is linear in the problem size. Our $2$-edge connectivity algorithm achieves the same parallel time as the connectivity algorithm of Andoni et al. (FOCS 2018). We also show an $\Omega(\log D')$ conditional lower bound for the biconnectivity problem.

Includes members:
  Member "simple concurrent labeling algorithms for connected components":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "concurrent disjoint set union")
  Member "simple graph coloring algorithms for congested clique and massively parallel computation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "graph coloring via degeneracy in streaming and other space conscious models")
  Member "matching and mis for uniformly sparse graphs in the low memory mpc model":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "batch dynamic algorithms via parallel change propagation and applications to dynamic trees")
  Member "massively parallel algorithms for finding well connected components in sparse graphs":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "equivalence classes and conditional hardness in massively parallel computations")
  Member "parallel graph connectivity in log diameter rounds":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "sparsifying distributed algorithms with ramifications in massively parallel computation and centralized local computation")
  Member "brief announcement semi mapreduce meets congested clique":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "graph sparsification for derandomizing massively parallel computation with low space")
  Member "massively parallel symmetry breaking on sparse graphs mis and maximal matching":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "near optimal massively parallel graph connectivity")
  Member "round compression for parallel graph algorithms in strongly sublinear space":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "dynamic graph algorithms with batch updates in the massively parallel computation model")

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.DS(Data Structures and Algorithms)