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: "deterministic distributed ruling sets of line graphs"
  Abstract: An $(\alpha,\beta)$-ruling set of a graph $G=(V,E)$ is a set $R\subseteq V$ such that for any node $v\in V$ there is a node $u\in R$ in distance at most $\beta$ from $v$ and such that any two nodes in $R$ are at distance at least $\alpha$ from each other. The concept of ruling sets can naturally be extended to edges, i.e., a subset $F\subseteq E$ is an $(\alpha,\beta)$-ruling edge set of a graph $G=(V,E)$ if the corresponding nodes form an $(\alpha,\beta)$-ruling set in the line graph of $G$. This paper presents a simple deterministic, distributed algorithm, in the $\mathsf{CONGEST}$ model, for computing $(2,2)$-ruling edge sets in $O(\log^* n)$ rounds. Furthermore, we extend the algorithm to compute ruling sets of graphs with bounded diversity. Roughly speaking, the diversity of a graph is the maximum number of maximal cliques a vertex belongs to. We devise $(2,O(\mathcal{D}))$-ruling sets on graphs with diversity $\mathcal{D}$ in $O(\mathcal{D}+\log^* n)$ rounds. This also implies a fast, deterministic $(2,O(\ell))$-ruling edge set algorithm for hypergraphs with rank at most $\ell$. #R##N#Furthermore, we provide a ruling set algorithm for general graphs that for any $B\geq 2$ computes an $\big(\alpha, \alpha \lceil \log_B n \rceil \big)$-ruling set in $O(\alpha \cdot B \cdot \log_B n)$ rounds in the $\mathsf{CONGEST}$ model. The algorithm can be modified to compute a $\big(2, \beta \big)$-ruling set in $O(\beta \Delta^{2/\beta} + \log^* n)$ rounds in the $\mathsf{CONGEST}$~ model, which matches the currently best known such algorithm in the more general $\mathsf{LOCAL}$ model.

Connected through hyperedge HE-1 (induced by source paper "near additive spanners in low polynomial deterministic congest time"):
  with members:
    - "improved deterministic distributed construction of spanners"
    - "efficient algorithms for constructing very sparse spanners and emulators"
    - "a hierarchy of lower bounds for sublinear additive spanners"
    - "hopsets with constant hopbound and applications to approximate shortest paths"
    - "a fast network decomposition algorithm and its applications to constant time distributed computation"
    - "the 4 3 additive spanner exponent is tight"
    - "a deterministic almost tight distributed algorithm for approximating single source shortest paths"

Connected through hyperedge HE-2 (induced by source paper "fast deterministic constructions of linear size spanners and skeletons"):
  with members:
    - "improved deterministic distributed construction of spanners"
    - "efficient algorithms for constructing very sparse spanners and emulators"
    - "a fast network decomposition algorithm and its applications to constant time distributed computation"
    - "parallel graph decompositions using random shifts"

Connected through hyperedge HE-3 (induced by source paper "distributed reconfiguration of maximal independent sets"):
  with members:
    - "reconfiguration of colorable sets in classes of perfect graphs"
    - "symmetry breaking in the congest model time and message efficient algorithms for ruling sets"
    - "an improved distributed algorithm for maximal independent set"
    - "the complexity of change"
    - "super fast 3 ruling sets"
    - "local computation lower and upper bounds"

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)