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: "a tale of santa claus hypergraphs and matroids"
  Abstract: A well-known problem in scheduling and approximation algorithms is the Santa Claus problem. Suppose that Santa Claus has a set of gifts, and he wants to distribute them among a set of children so that the least happy child is made as happy as possible. Here, the value that a child $i$ has for a present $j$ is of the form $p_{ij} \in \{ 0,p_j\}$. A polynomial time algorithm by Annamalai et al. gives a $12.33$-approximation and is based on a modification of Haxell's hypergraph matching argument. #R##N#In this paper, we introduce a matroid version of the Santa Claus problem. Our algorithm is also based on Haxell's augmenting tree, but with the introduction of the matroid structure we solve a more general problem with cleaner methods. Our result can then be used as a blackbox to obtain a $(4+\varepsilon)$-approximation for Santa Claus. This factor also compares against a natural, compact LP for Santa Claus.

Connected through hyperedge HE-1 (induced by source paper "approximating nash social welfare under submodular valuations through un matchings"):
  with members:
    - "on fair division of indivisible items"
    - "approximating the nash social welfare with budget additive valuations"
    - "finding fair and efficient allocations"
    - "convex program duality fisher markets and nash social welfare"
    - "nash social welfare for indivisible items under separable piecewise linear concave utilities"
    - "nash social welfare matrix permanent and stable polynomials"
    - "apx hardness of maximizing nash social welfare with indivisible items"
    - "combinatorial algorithm for restricted max min fair allocation"

Connected through hyperedge HE-2 (induced by source paper "inapproximability results for scheduling with interval and resource restrictions"):
  with members:
    - "local search breaks 1 75 for graph balancing"
    - "restricted max min fair allocation"
    - "structural parameters for scheduling with assignment restrictions"
    - "a quasi polynomial approximation for the restricted assignment problem"
    - "ptas for ordered instances of resource allocation problems with restrictions on inclusions"
    - "graph balancing with two edge types"
    - "a combinatorial approximation algorithm for graph balancing with light hyper edges"
    - "combinatorial algorithm for restricted max min fair allocation"

Connected through hyperedge HE-3 (induced by source paper "restricted max min allocation approximation and integrality gap"):
  with members:
    - "integrality gap of the configuration lp for the restricted max min fair allocation"
    - "restricted max min fair allocation"
    - "combinatorial algorithm for restricted max min fair allocation"
    - "quasi polynomial local search for restricted max min fair allocation"
    - "a new approximation technique for resource allocation problems"
    - "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)