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: "diameter spanner eccentricity spanner and approximating extremal graph distances static dynamic and fault tolerant"
  Abstract: The diameter, vertex eccentricities, and the radius of a graph are some of the most fundamental graph parameters. Roditty and Williams [STOC 2013] gave an $O(m\sqrt{n})$ time algorithm for computing a 1.5 approximation of graph diameter. We present the first non-trivial algorithm for maintaining `< 2'- approximation of graph diameter in dynamic setting. Our algorithm maintain a $(1.5+\epsilon)$ approximation of graph diameter that takes amortized update time of $O(\epsilon^{-1}n^{1.25})$ in partially dynamic setting. For graphs whose diameter remains bounded by some large constant, the total amortized time of our algorithm is $O(\epsilon^{-2}\sqrt{n})$, which almost matches the best known bound for static $1.5$-approximation of diameter. Backurs et al. [STOC 2018] gave an $\tilde O(m\sqrt{n})$ time algorithm for computing 2-approximation of eccentricities. They also showed that no $O(n^{2-o(1)})$ time algorithm can achieve an approximation factor better than $2$ for graph eccentricities, unless SETH fails. We present the $\tilde O(m)$ time algorithm for computing $2$-approximation of vertex eccentricities in directed weighted graphs. We also present fault tolerant data-structures for maintaining $1.5$-diameter and $2$-eccentricities.  We initiate the study of Extremal Distance Spanners. Given a graph G=(V,E), a subgraph H=(V,E0) is defined to be a {\em $t$-diameter-spanner} if the diameter of $H$ is at most $t$ times the diameter of $G$. We show that for any $n$-vertex directed graph $G$ we can compute a sparse subgraph $H$ which is a $(1.5)$-diameter-spanner of $G$ and contains at most $O(n^{1.5})$ edges. We also show that this bound is tight for graphs whose diameter is bounded by $n^{1/4-\epsilon}$. We present several other extremal-distance spanners with various size-stretch trade-offs. Finally, we extensively study these objects in the dynamic and fault-tolerant settings.

Connected through hyperedge HE-1 (induced by source paper "new algorithms and hardness for incremental single source shortest paths in directed graphs"):
  with members:
    - "decremental sssp in weighted digraphs faster and against an adaptive adversary"
    - "fully dynamic all pairs shortest paths improved worst case time and space bounds"
    - "deterministic algorithms for decremental approximate shortest paths faster and simpler"
    - "decremental strongly connected components and single source reachability in near linear time"
    - "graph pattern detection hardness for all induced patterns and faster non induced cycles"
    - "limits on all known and some unknown approaches to matrix multiplication"
    - "diameter spanners eccentricity spanners and approximating extremal distances"
    - "limits on the universal method for matrix multiplication"

Connected through hyperedge HE-2 (induced by source paper "deterministic algorithms for decremental approximate shortest paths faster and simpler"):
  with members:
    - "decremental sssp in weighted digraphs faster and against an adaptive adversary"
    - "fully dynamic all pairs shortest paths improved worst case time and space bounds"
    - "dynamic approximate shortest paths and beyond subquadratic and worst case update time"
    - "decremental strongly connected components and single source reachability in near linear time"
    - "algorithms and hardness for diameter in dynamic graphs"
    - "deterministic partially dynamic single source shortest paths in weighted graphs"
    - "thorup zwick emulators are universally optimal hopsets"
    - "tight hardness for shortest cycles and paths in sparse graphs"

Connected through hyperedge HE-3 (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-4 (induced by source paper "dynamic approximate shortest paths and beyond subquadratic and worst case update time"):
  with members:
    - "fully dynamic all pairs shortest paths improved worst case time and space bounds"
    - "dynamic matrix inverse improved algorithms and matching conditional lower bounds"
    - "sensitive distance and reachability oracles for large batch updates"
    - "towards tight approximation bounds for graph diameter and eccentricities"
    - "algorithms and hardness for diameter in dynamic graphs"
    - "a deamortization approach for dynamic spanner and dynamic maximal matching"
    - "deterministic partially dynamic single source shortest paths in weighted graphs"
    - "fully dynamic approximate maximum matching and minimum vertex cover in o log 3 n worst case update time"

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)