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: "algorithms for unipolar and generalized split graphs"
  Abstract: A graph $G=(V,E)$ is a {\it unipolar graph} if there exits a partition $V=V_1 \cup V_2$ such that, $V_1$ is a clique and $V_2$ induces the disjoint union of cliques. The complement-closed class of {\it generalized split graphs} are those graphs $G$ such that either $G$ {\it or} the complement of $G$ is unipolar. Generalized split graphs are a large subclass of perfect graphs. In fact, it has been shown that almost all $C_5$-free (and hence, almost all perfect graphs) are generalized split graphs. In this paper we present a recognition algorithm for unipolar graphs that utilizes a minimal triangulation of the given graph, and produces a partition when one exists. Our algorithm has running time O($nm^\prime$), where $m^\prime$ is the number of edges in a minimal triangulation of the given graph. Generalized split graphs can recognized via this algorithm in O($nm' + n\OL{m}'$) = O($n^3$) time. We give algorithms on unipolar graphs for finding a maximum independent set and a minimum clique cover in O($n+m$) time and for finding a maximum clique and a minimum proper coloring in O($n^{2.5}/\log n$), when a unipolar partition is given. These algorithms yield algorithms for the four optimization problems on generalized split graphs that have the same worst-case time bound. We also prove that the perfect code problem is NP-Complete for unipolar graphs.

Connected through hyperedge HE-1 (induced by source paper "solving partition problems almost always requires pushing many vertices around"):
  with members:
    - "recognition of unipolar and generalised split graphs"
    - "partitioning a graph into disjoint cliques and a triangle free graph"
    - "a polynomial kernel for proper interval vertex deletion"

Connected through hyperedge HE-2 (induced by source paper "on efficient domination for some classes of h free chordal graphs"):
  with members:
    - "polynomial time algorithms for weighted efficient domination problems in at free graphs and dually chordal graphs"
    - "bounding the clique width of h free chordal graphs"
    - "weighted efficient domination for p_6 free graphs in polynomial time"
    - "efficient domination for some subclasses of p_6 free graphs in polynomial time"
    - "weighted efficient domination for p_5 kp_2 free graphs in polynomial time"
    - "new polynomial cases of the weighted efficient domination problem"
    - "efficient dominating and edge dominating sets for graphs and hypergraphs"

Connected through hyperedge HE-3 (induced by source paper "parameterized algorithms for recognizing monopolar and 2 subcolorable graphs"):
  with members:
    - "recognition of unipolar and generalised split graphs"
    - "parameterized algorithms on perfect graphs for deletion to r ell graphs"

Connected through hyperedge HE-4 (induced by source paper "weighted efficient domination for p_6 free graphs in polynomial time"):
  with members:
    - "independence and efficient domination on p_6 free graphs"
    - "weighted efficient domination for p 5 free graphs in linear time"
    - "efficient domination for some subclasses of p_6 free graphs in polynomial time"
    - "weighted efficient domination for p_5 kp_2 free graphs in polynomial time"
    - "new polynomial cases of the weighted efficient domination problem"

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)