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: "an improved approximation guarantee for the maximum budgeted allocation problem"
  Abstract: We study the Maximum Budgeted Allocation problem, which is the problem of assigning indivisible items to players with budget constraints. In its most general form, an instance of the MBA problem might include many different prices for the same item among different players, and different budget constraints for every player. So far, the best approximation algorithms we know for the MBA problem achieve a $3/4$-approximation ratio, and employ a natural LP relaxation, called the Assignment-LP. In this paper, we give an algorithm for MBA, and prove that it achieves a $3/4+c$-approximation ratio, for some constant $c>0$. This algorithm works by rounding solutions to an LP called the Configuration-LP, therefore also showing that the Configuration-LP is strictly stronger than the Assignment-LP (for which we know that the integrality gap is $3/4$) for the MBA problem.

Connected through hyperedge HE-1 (induced by source paper "satiation in fisher markets and approximation of nash social welfare"):
  with members:
    - "near optimal online algorithms and fast approximation algorithms for resource allocation problems"
    - "a strongly polynomial algorithm for linear exchange markets"
    - "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"
    - "an improved combinatorial polynomial algorithm for the linear arrow debreu market"

Connected through hyperedge HE-2 (induced by source paper "approximating the nash social welfare with budget additive valuations"):
  with members:
    - "computing equilibria in markets with budget additive utilities"
    - "an improved combinatorial polynomial algorithm for the linear arrow debreu market"
    - "apx hardness of maximizing nash social welfare with indivisible items"
    - "combinatorial walrasian equilibrium"
    - "a combinatorial polynomial algorithm for the linear arrow debreu market"
    - "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)