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: "map graphs having witnesses of large girth"
  Abstract: Abstract   A half-square of a bipartite graph    B  =  (  X  ,  Y  ,    E    B    )    has one color class of B as vertex set, say X; two vertices are adjacent whenever they have a common neighbor in Y. If    G  =  (  V  ,    E    G    )    is the half-square of a planar bipartite graph    B  =  (  V  ,  W  ,    E    B    )   , then G is called a map graph, and B is a witness of G. Map graphs generalize planar graphs, and have been introduced and investigated by Chen, Grigni and Papadimitriou [STOC 1998, J. ACM 2002]. They proved that recognizing map graphs is in    NP    by proving the existence of a witness. Soon later, Thorup [FOCS 1998] claimed that recognizing map graphs is in    P   , by providing an    Ω  (    n    120    )   -time algorithm for n-vertex input graphs.  In this note, we give good characterizations and efficient recognition for half-squares of bipartite graphs with girth at least a given integer    g  ≥  8   . It turns out that map graphs having witnesses of girth at least g are precisely the graphs whose vertex-clique incidence bipartite graph is planar and of girth at least g. Our structural characterization implies an    O  (    n    2    m  )   -time algorithm for recognizing if a given n-vertex m-edge graph G is such a map graph.

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)