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 "detecting cliques in congest networks"):
  Abstract: The problem of detecting network structures plays a central role in distributed computing. One of the fundamental problems studied in this area is to determine whether for a given graph $H$, the input network contains a subgraph isomorphic to $H$ or not. We investigate this problem for $H$ being a clique $K_{l}$ in the classical distributed CONGEST model, where the communication topology is the same as the topology of the underlying network, and with limited communication bandwidth on the links. #R##N#Our first and main result is a lower bound, showing that detecting $K_{l}$ requires $\Omega(\sqrt{n} / b)$ communication rounds, for every $4 \le l \le \sqrt{n}$, and $\Omega(n / (l b))$ rounds for every $l \ge \sqrt{n}$, where $b$ is the bandwidth of the communication links. This result is obtained by using a reduction to the set disjointness problem in the framework of two-party communication complexity. #R##N#We complement our lower bound with a two-party communication protocol for listing all cliques in the input graph, which up to constant factors communicates the same number of bits as our lower bound for $K_4$ detection. This demonstrates that our lower bound cannot be improved using the two-party communication framework.

Includes members:
  Member "improved distributed expander decomposition and nearly optimal triangle enumeration":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a deterministic algorithm for balanced cut with applications to dynamic connectivity flows and beyond")
  Member "distributed triangle detection via expander decomposition":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "distributed testing of graph isomorphism in the congest model")
  Member "fooling views a new lower bound technique for distributed computations under congestion":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "distributed testing of graph isomorphism in the congest model")
  Member "distributed detection of cycles":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "distributed testing of graph isomorphism in the congest model")
  Member "quadratic and near quadratic lower bounds for the congest model":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "distributed maximum matching verification in congest")
  Member "triangle finding and listing in congest networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "distributed testing of graph isomorphism in the congest model")
  Member "deterministic subgraph detection in broadcast congest":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "distributed testing of graph isomorphism in the congest model")
  Member "tight bounds for distributed graph computations":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "sparse matrix multiplication with bandwidth restricted all to all communication")

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.DC(Distributed, Parallel, and Cluster Computing)