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: "approximation algorithms for non single minded profit maximization problems with limited supply"
  Abstract: We consider {\em profit-maximization} problems for {\em combinatorial auctions} with {\em non-single minded valuation functions} and {\em limited supply}. #R##N#We obtain fairly general results that relate the approximability of the profit-maximization problem to that of the corresponding {\em social-welfare-maximization} (SWM) problem, which is the problem of finding an allocation $(S_1,\ldots,S_n)$ satisfying the capacity constraints that has maximum total value $\sum_j v_j(S_j)$. For {\em subadditive valuations} (and hence {\em submodular, XOS valuations}), we obtain a solution with profit $\OPT_\swm/O(\log c_{\max})$, where $\OPT_\swm$ is the optimum social welfare and $c_{\max}$ is the maximum item-supply; thus, this yields an $O(\log c_{\max})$-approximation for the profit-maximization problem. Furthermore, given {\em any} class of valuation functions, if the SWM problem for this valuation class has an LP-relaxation (of a certain form) and an algorithm "verifying" an {\em integrality gap} of $\al$ for this LP, then we obtain a solution with profit $\OPT_\swm/O(\al\log c_{\max})$, thus obtaining an $O(\al\log c_{\max})$-approximation. #R##N#For the special case, when the tree is a path, we also obtain an incomparable $O(\log m)$-approximation (via a different approach) for subadditive valuations, and arbitrary valuations with unlimited supply. Our approach for the latter problem also gives an $\frac{e}{e-1}$-approximation algorithm for the multi-product pricing problem in the Max-Buy model, with limited supply, improving on the previously known approximation factor of 2.

Connected through hyperedge HE-1 (induced by source paper "graph pricing with limited supply"):
  with members:
    - "exact algorithms and lower bounds for stable instances of euclidean k means"
    - "hardness of graph pricing through generalized max dicut"
    - "independent set induced matching and pricing connections and tight subexponential time approximation hardnesses"
    - "a sublogarithmic approximation for highway and tollbooth pricing"

Connected through hyperedge HE-2 (induced by source paper "price doubling and item halving robust revenue guarantees for item pricing"):
  with members:
    - "a duality based unified approach to bayesian mechanism design"
    - "simple mechanisms for subadditive buyers via duality"
    - "envy free pricing in multi unit markets"
    - "mechanism design for subadditive agents via an ex ante relaxation"
    - "pricing to maximize revenue and welfare simultaneously in large markets"
    - "on the computational complexity of optimal simple mechanisms"
    - "on welfare approximation and stable pricing"
    - "secretary problems with non uniform arrival order"

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.GT(Computer Science and Game Theory)