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: "linear time split decomposition revisited"
  Abstract: Given a family F of subsets of a ground set V, its orthogonal is defined to be the family of subsets that do not overlap any element of F. #R##N#Using this tool we revisit the problem of designing a simple linear time algorithm for undirected graph split (also known as 1-join) decomposition.

Connected through hyperedge HE-1 (induced by source paper "a quasi linear time b matching algorithm on distance hereditary graphs and bounded split width graphs"):
  with members:
    - "parameterized aspects of triangle enumeration"
    - "fully polynomial fpt algorithms for some classes of bounded clique width graphs"
    - "the weighted matching approach to maximum cardinality matching"
    - "on the power of tree depth for fully polynomial fpt algorithms"
    - "when can graph hyperbolicity be computed in linear time"
    - "a linear time algorithm for maximum cardinality matching on cocomparability graphs"
    - "data structures for weighted matching and extensions to b matching and f factors"
    - "fully polynomial time parameterized computations for graphs and matrices of low treewidth"

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"
    - "the power of data reduction for matching"
    - "tight hardness results for distance and centrality problems in constant degree graphs"
    - "fully polynomial time parameterized computations for graphs and matrices of low treewidth"

Connected through hyperedge HE-3 (induced by source paper "solving problems on graphs of high rank width"):
  with members:
    - "meta kernelization using well structured modulators"
    - "on feedback vertex set new measure and new structures"
    - "chordal editing is fixed parameter tractable"
    - "kernelization using structural parameters on sparse graph classes"
    - "meta kernelization with structural parameters"
    - "backdoors to satisfaction"
    - "practical and efficient split decomposition via graph labelled trees"
    - "kernel bounds for path and cycle problems"

Connected through hyperedge HE-4 (induced by source paper "between treewidth and clique width"):
  with members:
    - "solving hamiltonian cycle by an ept algorithm for a non sparse parameter"
    - "parameterized algorithms for modular width"
    - "lower bounds for the complexity of monadic second order logic"

Connected through hyperedge HE-5 (induced by source paper "on polygon numbers of circle graphs and distance hereditary graphs"):
  with members:
    - "practical and efficient circle graph recognition"

Connected through hyperedge HE-6 (induced by source paper "on complexities of minus domination"):
  with members:
    - "signed and minus domination in complete multipartite graphs"
    - "kernels for connected dominating set on graphs with excluded topological subgraphs"
    - "practical and efficient split decomposition via graph labelled trees"
    - "linear time algorithms for graphs of bounded rankwidth a fresh look using game theory"
    - "linear time algorithms for finding a dominating set of fixed size in degenerated graphs"

Connected through hyperedge HE-7 (induced by source paper "meta kernelization with structural parameters"):
  with members:
    - "meta kernelization using well structured modulators"
    - "guarantees and limits of preprocessing in constraint satisfaction and reasoning"
    - "kernelization using structural parameters on sparse graph classes"
    - "preprocessing for treewidth a combinatorial analysis through kernelization"

Connected through hyperedge HE-8 (induced by source paper "detecting 2 joins faster"):
  with members:
    - "combinatorial optimization with 2 joins"

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.DM(Discrete Mathematics)