human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "plane gossip approximating rumor spread in planar graphs"
  Abstract: We study the design of schedules for multi-commodity multicast. In this problem, we are given an undirected graph $G$ and a collection of source-destination pairs, and the goal is to schedule a minimum-length sequence of matchings that connects every source with its respective destination. Multi-commodity multicast models a classic information dissemination problem in networks where the primary communication constraint is the number of connections that a given node can make, not link bandwidth. Multi-commodity multicast and its special cases, broadcast and multicast, are all NP-complete and the best approximation factors known are $2^{\widetilde{O}(\sqrt{\log n})}$, $O(\log n/\log\log n)$, and $O(\log k/\log\log k)$, respectively, where $n$ is the number of nodes and $k$ is the number of terminals in the multicast instance. #R##N#Multi-commodity multicast is closely related to the problem of finding a subgraph of optimal poise, where the poise is defined as the sum of the maximum degree of the subgraph and the maximum distance between any source-destination pair in the subgraph. We first show that for any instance of the multicast problem, the minimum poise subgraph can be approximated to within a factor of $O(\log k \log n)$ with respect to the value of a natural LP relaxation in an $n$-node graph with $k$ source-destination pairs. This is the first upper bound on the integrality gap of the natural LP; all previous algorithms, both combinatorial and LP-based, yielded approximations with respect to the integer optimum. Using this integrality gap upper bound, we obtain our main result: an $O(\log^2 k\log^2 n)$-approximation for multi-commodity multicast for planar graphs. In addition, the techniques used also give an $O(\log^2 n)$-approximation for radio gossip in planar graphs. This is the first bound for radio gossip given that doesn't rely on the maximum degree of the graph.

Connected through hyperedge HE-1 (induced by source paper "near optimal schedules for simultaneous multicasts"):
  with members:
    - "improved distributed approximations for minimum weight two edge connected spanning subgraph"
    - "round and message optimal distributed graph algorithms"
    - "minor excluded network families admit fast distributed algorithms"
    - "new distributed algorithms in almost mixing time via transformations from parallel algorithms"
    - "low congestion shortcuts without embedding"
    - "a simpler proof for o congestion dilation packet routing"

Question: Please tell me which class the center node 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)