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: "towards tight approximation bounds for graph diameter and eccentricities"
  Abstract: Among the most important graph parameters is the Diameter, the largest distance between any two vertices. There are no known very efficient algorithms for computing the Diameter exactly. Thus, much research has been devoted to how fast this parameter can be approximated. Chechik et al. showed that the diameter can be approximated within a multiplicative factor of $3/2$ in $\tilde{O}(m^{3/2})$ time. Furthermore, Roditty and Vassilevska W. showed that unless the Strong Exponential Time Hypothesis (SETH) fails, no $O(n^{2-\epsilon})$ time algorithm can achieve an approximation factor better than $3/2$ in sparse graphs. Thus the above algorithm is essentially optimal for sparse graphs for approximation factors less than $3/2$. It was, however, completely plausible that a $3/2$-approximation is possible in linear time. In this work we conditionally rule out such a possibility by showing that unless SETH fails no $O(m^{3/2-\epsilon})$ time algorithm can achieve an approximation factor better than $5/3$. #R##N#Another fundamental set of graph parameters are the Eccentricities. The Eccentricity of a vertex $v$ is the distance between $v$ and the farthest vertex from $v$. Chechik et al. showed that the Eccentricities of all vertices can be approximated within a factor of $5/3$ in $\tilde{O}(m^{3/2})$ time and Abboud et al. showed that no $O(n^{2-\epsilon})$ algorithm can achieve better than $5/3$ approximation in sparse graphs. We show that the runtime of the $5/3$ approximation algorithm is also optimal under SETH. We also show that no near-linear time algorithm can achieve a better than $2$ approximation for the Eccentricities and that this is essentially tight: we give an algorithm that approximates Eccentricities within a $2+\delta$ factor in $\tilde{O}(m/\delta)$ time for any $0<\delta<1$. This beats all Eccentricity algorithms in Cairo et al.

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 "fast approximate shortest paths in the congested clique"):
  with members:
    - "delta 1 coloring in the congested clique model"
    - "congested clique algorithms for graph spanners"
    - "sparse matrix multiplication and triangle listing in the congested clique model"
    - "a deterministic distributed algorithm for exact weighted all pairs shortest paths in tilde o n 3 2 rounds"
    - "distributed triangle detection via expander decomposition"
    - "distributed exact weighted all pairs shortest paths in near linear time"
    - "mst in o 1 rounds of the congested clique"
    - "linear size hopsets with small hopbound and distributed routing with low memory"

Connected through hyperedge HE-3 (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"
    - "algorithms and hardness for diameter in dynamic graphs"
    - "diameter spanner eccentricity spanner and approximating extremal graph distances static dynamic and fault tolerant"
    - "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"

Connected through hyperedge HE-4 (induced by source paper "diameter computation on h minor free graphs and graphs of bounded distance vc dimension"):
  with members:
    - "planar diameter via metric compression"
    - "fast diameter computation within split graphs"
    - "solving linear programs in the current matrix multiplication time"
    - "multivariate analysis of orthogonal range searching and graph distances parameterized by treewidth"
    - "fully polynomial fpt algorithms for some classes of bounded clique width graphs"
    - "voronoi diagrams on planar graphs and computing the diameter in deterministic tilde o n 5 3 time"
    - "subquadratic algorithms for the diameter and the sum of pairwise distances in planar graphs"
    - "on the hardness of partially dynamic graph problems and connections to diameter"

Connected through hyperedge HE-5 (induced by source paper "approximation algorithms for min distance problems"):
  with members:
    - "faster all pairs shortest paths via circuit complexity"
    - "approximating the diameter of planar graphs in near linear time"
    - "computing the diameter polynomially faster than apsp"
    - "subgraph isomorphism in planar graphs and related problems"

Connected through hyperedge HE-6 (induced by source paper "tight approximation algorithms for bichromatic graph diameter and related problems"):
  with members:
    - "on pairwise spanners"
    - "fast computation of empirically tight bounds for the diameter of massive graphs"

Connected through hyperedge HE-7 (induced by source paper "parameterized complexity of diameter"):
  with members:
    - "towards improving brandes algorithm for betweenness centrality"
    - "data reduction for maximum matching on real world graphs theory and experiments"
    - "multivariate analysis of orthogonal range searching and graph distances parameterized by treewidth"
    - "efficient and adaptive parameterized algorithms on modular decompositions"
    - "parameterized aspects of triangle enumeration"
    - "fully polynomial fpt algorithms for some classes of bounded clique width graphs"
    - "voronoi diagrams on planar graphs and computing the diameter in deterministic tilde o n 5 3 time"
    - "when can graph hyperbolicity be computed in linear time"

Connected through hyperedge HE-8 (induced by source paper "algorithms and hardness for diameter in dynamic graphs"):
  with members:
    - "graph pattern detection hardness for all induced patterns and faster non induced cycles"
    - "a note on hardness of diameter approximation"
    - "conditional hardness for sensitivity problems"
    - "near linear lower bounds for distributed distance computations even in sparse networks"
    - "unifying and strengthening hardness for dynamic problems via the online matrix vector multiplication conjecture"
    - "decremental single source shortest paths on undirected graphs in near linear total update time"
    - "powers of tensors and fast matrix multiplication"
    - "popular conjectures imply strong lower bounds for dynamic problems"

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)