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: "efficient computation of distance sketches in distributed networks"
  Abstract: Distance computation is one of the most fundamental primitives used in communication networks. The cost of effectively and accurately computing pairwise network distances can become prohibitive in large-scale networks such as the Internet and Peer-to-Peer (P2P) networks. To negotiate the rising need for very efficient distance computation, approximation techniques for numerous variants of this question have recently received significant attention in the literature. The goal is to preprocess the graph and store a small amount of information such that whenever a query for any pairwise distance is issued, the distance can be well approximated (i.e., with small stretch) very quickly in an online fashion. Specifically, the pre-processing (usually) involves storing a small sketch with each node, such that at query time only the sketches of the concerned nodes need to be looked up to compute the approximate distance. In this paper, we present the first theoretical study of distance sketches derived from distance oracles in a distributed network. We first present a fast distributed algorithm for computing approximate distance sketches, based on a distributed implementation of the distance oracle scheme of [Thorup-Zwick, JACM 2005]. We also show how to modify this basic construction to achieve different tradeoffs between the number of pairs for which the distance estimate is accurate and other parameters. These tradeoffs can then be combined to give an efficient construction of small sketches with provable average-case as well as worst-case performance. Our algorithms use only small-sized messages and hence are suitable for bandwidth-constrained networks, and can be used in various networking applications such as topology discovery and construction, token management, load balancing, monitoring overlays, and several other problems in distributed algorithms.

Connected through hyperedge HE-1 (induced by source paper "a deterministic almost tight distributed algorithm for approximating single source shortest paths"):
  with members:
    - "algebraic methods in the congested clique"
    - "decremental single source shortest paths on undirected graphs in near linear total update time"
    - "approximation of distances and shortest paths in the broadcast congest clique"
    - "fast partial distance estimation and applications"
    - "almost tight distributed minimum cut algorithms"
    - "distributed approximation algorithms for weighted shortest paths"
    - "distributed minimum cut approximation"
    - "tight bounds for distributed minimum weight spanning tree verification"

Connected through hyperedge HE-2 (induced by source paper "distributed approximation algorithms for weighted shortest paths"):
  with members:
    - "brief announcement almost tight approximation distributed algorithm for minimum cut"
    - "distributed minimum cut approximation"
    - "distributed random walks"
    - "tight bounds for distributed minimum weight spanning tree verification"
    - "super fast distributed algorithms for metric facility location"
    - "optimal deterministic routing and sorting on the congested clique"
    - "tri tri again finding triangles and small subgraphs in a distributed setting"
    - "notions of connectivity in overlay networks"

Connected through hyperedge HE-3 (induced by source paper "fast partial distance estimation and applications"):
  with members:
    - "an almost tight distributed algorithm for computing single source shortest paths"
    - "approximation of distances and shortest paths in the broadcast congest clique"
    - "distributed approximation algorithms for weighted shortest paths"
    - "improved distributed steiner forest construction"
    - "distributed verification and hardness of distributed approximation"
    - "faster approximation schemes for fractional multicommodity flow problems via dynamic graph algorithms"
    - "all pairs shortest paths using bridging sets and rectangular matrix multiplication"

Connected through hyperedge HE-4 (induced by source paper "fast routing table construction using small messages"):
  with members:
    - "distributed verification and hardness of distributed approximation"

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)