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: "tight hardness results for distance and centrality problems in constant degree graphs"
  Abstract: Finding important nodes in a graph and measuring their importance is a fundamental problem in the analysis of social networks, transportation networks, biological systems, etc. Among popular such metrics are graph centrality, betweenness centrality (BC), and reach centrality (RC). These measures are also very related to classic notions like diameter and radius. Roditty and Vassilevska Williams~[STOC'13] showed that no algorithm can compute a (3/2-\delta)-approximation of the diameter in sparse and unweighted graphs faster that n^{2-o(1)} time unless the widely believed strong exponential time hypothesis (SETH) is false. Abboud et al.~[SODA'15] and [SODA'16] further analyzed these problems under the recent line of research on hardness in P. They showed that in sparse and unweighted graphs (weighted for BC) none of these problems can be solved faster than n^{2-o(1)} unless some popular conjecture is false. Furthermore they ruled out a (2-\delta)-approximation for RC, a (3/2-\delta)-approximation for Radius and a (5/3-\delta)-approximation for computing all eccentricities of a graph for any \delta > 0. We extend these results to the case of unweighted graphs with constant maximum degree. Through new graph constructions we are able to obtain the same approximation and time bounds as for sparse graphs even in unweighted bounded-degree graphs. We show that no (3/2-\delta) approximation of Radius or Diameter, (2-\delta)-approximation of RC, (5/3-\delta)-approximation of all eccentricities or exact algorithm for BC exists in time n^{2-o(1)} for such graphs and any \delta > 0. This strengthens the result for BC of Abboud et al.~[SODA'16] by showing a hardness result for unweighted graphs, and follows in the footsteps of Abboud et al.~[SODA'16] and Abboud and Dahlgaard~[FOCS'16] in showing conditional lower bounds for restricted but realistic graph classes.

Connected through hyperedge HE-1 (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"
    - "towards tight approximation bounds for graph diameter and eccentricities"
    - "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"

Connected through hyperedge HE-2 (induced by source paper "parameterized complexity of diameter"):
  with members:
    - "towards improving brandes algorithm for betweenness centrality"
    - "towards tight approximation bounds for graph diameter and eccentricities"
    - "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"

Connected through hyperedge HE-3 (induced by source paper "fully polynomial fpt algorithms for some classes of bounded clique width graphs"):
  with members:
    - "the use of a pruned modular decomposition for maximum matching algorithms on some graph classes"
    - "efficient and adaptive parameterized algorithms on modular decompositions"
    - "parameterized aspects of triangle enumeration"
    - "on the power of tree depth for fully polynomial fpt algorithms"
    - "when can graph hyperbolicity be computed in linear time"
    - "the power of data reduction for matching"
    - "fully polynomial time parameterized computations for graphs and matrices of low treewidth"
    - "polynomial fixed parameter algorithms a case study for longest path on interval 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)