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: "dense subgraphs on dynamic networks"
  Abstract: In distributed networks, it is often useful for the nodes to be aware of dense subgraphs, e.g., such a dense subgraph could reveal dense subtructures in otherwise sparse graphs (e.g. the World Wide Web or social networks); these might reveal community clusters or dense regions for possibly maintaining good communication infrastructure. In this work, we address the problem of self-awareness of nodes in a dynamic network with regards to graph density, i.e., we give distributed algorithms for maintaining dense subgraphs that the member nodes are aware of. The only knowledge that the nodes need is that of the dynamic diameter $D$, i.e., the maximum number of rounds it takes for a message to traverse the dynamic network. For our work, we consider a model where the number of nodes are fixed, but a powerful adversary can add or remove a limited number of edges from the network at each time step. The communication is by broadcast only and follows the CONGEST model. Our algorithms are continuously executed on the network, and at any time (after some initialization) each node will be aware if it is part (or not) of a particular dense subgraph. We give algorithms that ($2 + \epsilon$)-approximate the densest subgraph and ($3 + \epsilon$)-approximate the at-least-$k$-densest subgraph (for a given parameter $k$). Our algorithms work for a wide range of parameter values and run in $O(D\log_{1+\epsilon} n)$ time. Further, a special case of our results also gives the first fully decentralized approximation algorithms for densest and at-least-$k$-densest subgraph problems for static distributed graphs.

Connected through hyperedge HE-1 (induced by source paper "distributed edge connectivity in sublinear time"):
  with members:
    - "improved distributed expander decomposition and nearly optimal triangle enumeration"
    - "small cuts and connectivity certificates a fault tolerant approach"
    - "distributed triangle detection via expander decomposition"
    - "graph sparsification spectral sketches and faster resistance computation via short cycle decompositions"
    - "distributed exact weighted all pairs shortest paths in near linear time"
    - "expander decomposition and pruning faster stronger and simpler"
    - "a faster distributed single source shortest paths algorithm"
    - "distributed exact shortest paths in sublinear time"

Connected through hyperedge HE-2 (induced by source paper "near optimal fully dynamic densest subgraph"):
  with members:
    - "distributed dense subgraph detection and low outdegree orientation"
    - "new algorithms and lower bounds for all pairs max flow in undirected graphs"
    - "inapproximability of maximum biclique problems minimum k cut and densest at least k subgraph from the small set expansion hypothesis"
    - "fully dynamic approximate maximum matching and minimum vertex cover in o log 3 n worst case update time"
    - "egalitarian graph orientations"
    - "the ubiquity of large graphs and surprising challenges of graph processing"
    - "new deterministic approximation algorithms for fully dynamic matching"
    - "popular conjectures as a barrier for dynamic planar graph algorithms"

Connected through hyperedge HE-3 (induced by source paper "distributed dense subgraph detection and low outdegree orientation"):
  with members:
    - "near optimal fully dynamic densest subgraph"
    - "improved distributed expander decomposition and nearly optimal triangle enumeration"
    - "distributed approximation algorithms for maximum matching in graphs and hypergraphs"
    - "improved deterministic distributed matching via rounding"
    - "improved distributed degree splitting and edge coloring"
    - "on derandomizing local distributed algorithms"
    - "distributed degree splitting edge coloring and orientations"
    - "densest subgraph in dynamic graph streams"

Connected through hyperedge HE-4 (induced by source paper "distributed exact weighted all pairs shortest paths in near linear time"):
  with members:
    - "distributed edge connectivity in sublinear time"
    - "a deterministic distributed algorithm for exact weighted all pairs shortest paths in tilde o n 3 2 rounds"
    - "new and simplified distributed algorithms for weighted all pairs shortest paths"
    - "a deterministic distributed algorithm for weighted all pairs shortest paths through pipelining"
    - "a faster distributed single source shortest paths algorithm"
    - "distributed exact shortest paths in sublinear time"
    - "distributed exact weighted all pairs shortest paths in tilde o n 5 4 rounds"
    - "improved distributed algorithms for exact shortest paths"

Connected through hyperedge HE-5 (induced by source paper "distributed computation of large scale graph problems"):
  with members:
    - "fast distributed pagerank computation"
    - "distributed approximation algorithms for weighted shortest paths"
    - "when distributed computation is communication expensive"
    - "can quantum communication speed up distributed computation"
    - "streaming balanced graph partitioning for random graphs"
    - "tri tri again finding triangles and small subgraphs in a distributed setting"
    - "sublinear bounds for randomized leader election"
    - "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.DC(Distributed, Parallel, and Cluster Computing)