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 "distributed approximation algorithms for steiner tree in the mathcal congested mathcal clique"):
  Abstract: The \emph{Steiner tree} problem is one of the fundamental and classical problems in combinatorial optimization. In this paper, we study this problem in the $\mathcal{CONGESTED}$ $\mathcal{CLIQUE}$ model of distributed computing and present two deterministic distributed approximation algorithms for the same. The first algorithm computes a Steiner tree in $\tilde{O}(n^{1/3})$ rounds and $\tilde{O}(n^{7/3})$ messages for a given connected undirected weighted graph of $n$ nodes. Note here that $\tilde{O}(\cdot)$ notation hides polylogarithmic factors in $n$. The second one computes a Steiner tree in $O(S + \log\log n)$ rounds and $O(S (n - t)^2 + n^2)$ messages, where $S$ and $t$ are the \emph{shortest path diameter} and the number of \emph{terminal} nodes respectively in the given input graph. Both the algorithms admit an approximation factor of $2(1 - 1/\ell)$, where $\ell$ is the number of terminal leaf nodes in the optimal Steiner tree. For graphs with $S = \omega(n^{1/3} \log n)$, the first algorithm exhibits better performance than the second one in terms of the round complexity. On the other hand, for graphs with $S = \tilde{o}(n^{1/3})$, the second algorithm outperforms the first one in terms of the round complexity. In fact when $S = O(\log\log n)$ then the second algorithm admits a round complexity of $O(\log\log n)$ and message complexity of $\tilde{O}(n^2)$. To the best of our knowledge, this is the first work to study the Steiner tree problem in the $\mathcal{CONGESTED}$ $\mathcal{CLIQUE}$ model.

Includes members:
  Member "connectivity lower bounds in broadcast congested clique":
    also connected through other hyperedges:
      (none)
  Member "mst in o 1 rounds of the congested clique":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "how fast can you update your mst dynamic algorithms for cluster computing")
  Member "super fast mst algorithms in the congested clique using o m messages":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "sparse matrix multiplication with bandwidth restricted all to all communication")
  Member "algebraic methods in the congested clique":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "exponentially faster shortest paths in the congested clique")
  Member "approximation of distances and shortest paths in the broadcast congest clique":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "exponentially faster shortest paths in the congested clique")
  Member "fast partial distance estimation and applications":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "fast approximate shortest paths in the congested clique")
  Member "distributed approximation algorithms for weighted shortest paths":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "distributed edge connectivity in sublinear time")
  Member "near constant time distributed algorithms on a congested clique":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "simple graph coloring algorithms for congested clique and massively parallel computation")

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)