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: "distance preserving subgraphs of interval graphs"
  Abstract: We consider the problem of finding small distance-preserving subgraphs of undirected, unweighted interval graphs with $k$ terminal vertices. #R##N#To start with, we show that finding an optimal distance-preserving subgraph is $\mathsf{NP}$-hard for general graphs. Then, we show that every interval graph admits a subgraph with $O(k)$ branching vertices that approximates pairwise terminal distances up to an additive term of $+1$. We also present an interval graph $G_{\mathrm{int}}$ for which the $+1$ approximation is necessary to obtain the $O(k)$ upper bound on the number of branching vertices. In particular, any distance-preserving subgraph of $G_{\mathrm{int}}$ has $\Omega(k\log k)$ branching vertices. Furthermore, we prove that every interval graph admits a distance-preserving subgraph with $O(k\log k)$ branching vertices, implying that the $\Omega(k\log k)$ lower bound for interval graphs is tight. To conclude, we show that there exists an interval graph such that every optimal distance-preserving subgraph of it has $O(k)$ branching vertices and $\Omega(k\log k)$ branching edges, thereby providing a separation between branching vertices and branching edges. #R##N#The $O(k)$ bound for distance-approximating subgraphs follows from a na\"ive analysis of shortest paths in interval graphs. $G_{\mathrm{int}}$ is constructed using bit-reversal permutation matrices. The $O(k\log k)$ bound for distance-preserving subgraphs uses a divide-and-conquer approach. Finally, the separation between branching vertices and branching edges employs Hansel's lemma for graph covering.

Connected through hyperedge HE-1 (induced by source paper "graph spanners a tutorial review"):
  with members:
    - "near additive spanners and near exact hopsets a unified view"
    - "some general structure for extremal sparsification problems"
    - "weighted additive spanners"
    - "near additive spanners in low polynomial deterministic congest time"
    - "multi level graph sketches via single level solvers"
    - "almost shortest paths and pram distance oracles in weighted graphs"
    - "an fpt algorithm for minimum additive spanner problem"
    - "distributed construction of light networks"

Connected through hyperedge HE-2 (induced by source paper "minimizing branching vertices in distance preserving subgraphs"):
  with members:
    - "steiner point removal with distortion o log k"
    - "linear size distance preservers"
    - "vertex sparsifiers new results from old techniques"
    - "preserving terminal distances using minors"
    - "vertex sparsifiers and abstract rounding algorithms"
    - "spectral sparsification of graphs"

Connected through hyperedge HE-3 (induced by source paper "linear size distance preservers"):
  with members:
    - "thorup zwick emulators are universally optimal hopsets"
    - "multiple source dual fault tolerant bfs trees"
    - "a hierarchy of lower bounds for sublinear additive spanners"
    - "a linear size logarithmic stretch path reporting distance oracle for general graphs"
    - "dual failure resilient bfs structure"
    - "very sparse additive spanners and emulators"
    - "better distance preservers and additive spanners"
    - "sublinear distance labeling for sparse graphs"

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)