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: "the power of data reduction for matching"
  Abstract: Finding maximum-cardinality matchings in undirected graphs is arguably one of the most central graph primitives. For $m$-edge and $n$-vertex graphs, it is well-known to be solvable in $O(m\sqrt{n})$ time; however, for several applications this running time is still too slow. We investigate how linear-time (and almost linear-time) data reduction (used as preprocessing) can alleviate the situation. More specifically, we focus on (almost) linear-time kernelization. We start a deeper and systematic study both for general graphs and for bipartite graphs. Our data reduction algorithms easily comply (in form of preprocessing) with every solution strategy (exact, approximate, heuristic), thus making them attractive in various settings.

Connected through hyperedge HE-1 (induced by source paper "efficient and adaptive parameterized algorithms on modular decompositions"):
  with members:
    - "parameterized aspects of triangle enumeration"
    - "fully polynomial fpt algorithms for some classes of bounded clique width graphs"
    - "on the power of tree depth for fully polynomial fpt algorithms"
    - "when can graph hyperbolicity be computed in linear time"
    - "data structures for weighted matching and extensions to b matching and f factors"
    - "quadratic conditional lower bounds for string problems and dynamic time warping"
    - "polynomial fixed parameter algorithms a case study for longest path on interval graphs"
    - "why walking the dog takes time frechet distance has no strongly subquadratic algorithms unless seth fails"

Connected through hyperedge HE-2 (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"
    - "tight hardness results for distance and centrality problems in constant degree graphs"
    - "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"

Connected through hyperedge HE-3 (induced by source paper "kernelization lower bounds for finding constant size subgraphs"):
  with members:
    - "when can graph hyperbolicity be computed in linear time"
    - "linear time kernelization for feedback vertex set"
    - "diminishable parameterized problems and strict polynomial kernelization"
    - "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"
    - "why walking the dog takes time frechet distance has no strongly subquadratic algorithms unless seth fails"
    - "popular conjectures imply strong lower bounds for dynamic problems"
    - "kernelization lower bounds by cross composition"

Connected through hyperedge HE-4 (induced by source paper "on the power of tree depth for fully polynomial fpt algorithms"):
  with members:
    - "data structures for weighted matching and extensions to b matching and f factors"
    - "fast exact shortest path distance queries on large networks by pruned landmark labeling"

Connected through hyperedge HE-5 (induced by source paper "polynomial fixed parameter algorithms a case study for longest path on interval graphs"):
  with members:
    - "fully polynomial time parameterized computations for graphs and matrices of low treewidth"
    - "approximation and fixed parameter subquadratic algorithms for radius and diameter"
    - "why walking the dog takes time frechet distance has no strongly subquadratic algorithms unless seth fails"
    - "popular conjectures imply strong lower bounds for dynamic problems"
    - "efficient computation of representative sets with applications in parameterized and exact algorithms"
    - "a nearly mlogn time solver for sdd linear systems"
    - "a simple polynomial algorithm for the longest path problem on cocomparability graphs"
    - "narrow sieves for parameterized paths and packings"

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)