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: "finding perfect matchings in bipartite hypergraphs"
  Abstract: Haxell's condition is a natural hypergraph analog of Hall's condition, which is a well-known necessary and sufficient condition for a bipartite graph to admit a perfect matching. That is, when Haxell's condition holds it forces the existence of a perfect matching in the bipartite hypergraph. Unlike in graphs, however, there is no known polynomial time algorithm to find the hypergraph perfect matching that is guaranteed to exist when Haxell's condition is satisfied. #R##N#We prove the existence of an efficient algorithm to find perfect matchings in bipartite hypergraphs whenever a stronger version of Haxell's condition holds. Our algorithm can be seen as a generalization of the classical Hungarian algorithm for finding perfect matchings in bipartite graphs. The techniques we use to achieve this result could be of use more generally in other combinatorial problems on hypergraphs where disjointness structure is crucial, e.g. Set Packing.

Connected through hyperedge HE-1 (induced by source paper "hierarchical decomposition mechanism by konig egervary layer subgraph with application on vertex cover"):
  with members:
    - "core influence mechanism on vertex cover problem through leaf removal core breaking"
    - "modeling polypharmacy side effects with graph convolutional networks"
    - "higher order organization of complex networks"
    - "research on solution space of bipartite graph vertex cover by maximum matchings"
    - "evolution of the internet k dense structure"
    - "threshold values of random k sat from the cavity method"

Connected through hyperedge HE-2 (induced by source paper "algorithms for weighted independent transversals and strong colouring"):
  with members:
    - "lopsidependency in the moser tardos framework beyond the lopsided lovasz local lemma"
    - "algorithmic and enumerative aspects of the moser tardos distribution"
    - "new constructive aspects of the lovasz local lemma"
    - "deterministic algorithms for the lovasz local lemma"
    - "a constructive proof of the general lovasz local lemma"

Connected through hyperedge HE-3 (induced by source paper "a tale of santa claus hypergraphs and matroids"):
  with members:
    - "integrality gap of the configuration lp for the restricted max min fair allocation"
    - "local search breaks 1 75 for graph balancing"
    - "restricted max min fair allocation"
    - "santa claus schedules jobs on unrelated machines"
    - "on allocating goods to maximize fairness"

Connected through hyperedge HE-4 (induced by source paper "combinatorial algorithm for restricted max min fair allocation"):
  with members:
    - "quasi polynomial local search for restricted max min fair allocation"
    - "a new approximation technique for resource allocation problems"
    - "santa claus schedules jobs on unrelated machines"
    - "new constructive aspects of the lovasz local lemma"
    - "on allocating goods to maximize fairness"

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)