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: "truthful mechanism design for multidimensional covering problems"
  Abstract: We investigate {\em multidimensional covering mechanism-design} problems, wherein there are $m$ items that need to be covered and $n$ agents who provide covering objects, with each agent $i$ having a private cost for the covering objects he provides. The goal is to select a set of covering objects of minimum total cost that together cover all the items. #R##N#We focus on two representative covering problems: uncapacitated facility location (\ufl) and vertex cover (\vcp). For multidimensional \ufl, we give a black-box method to transform any {\em Lagrangian-multiplier-preserving} $\rho$-approximation algorithm for \ufl to a truthful-in-expectation, $\rho$-approx. mechanism. This yields the first result for multidimensional \ufl, namely a truthful-in-expectation 2-approximation mechanism. #R##N#For multidimensional \vcp (\mvcp), we develop a {\em decomposition method} that reduces the mechanism-design problem into the simpler task of constructing {\em threshold mechanisms}, which are a restricted class of truthful mechanisms, for simpler (in terms of graph structure or problem dimension) instances of \mvcp. By suitably designing the decomposition and the threshold mechanisms it uses as building blocks, we obtain truthful mechanisms with the following approximation ratios ($n$ is the number of nodes): (1) $O(r^2\log n)$ for $r$-dimensional \vcp; and (2) $O(r\log n)$ for $r$-dimensional \vcp on any proper minor-closed family of graphs (which improves to $O(\log n)$ if no two neighbors of a node belong to the same player). These are the first truthful mechanisms for \mvcp with non-trivial approximation guarantees.

Connected through hyperedge HE-1 (induced by source paper "data centric mobile crowdsensing"):
  with members:
    - "scalable mobile crowdsensing via peer to peer data sharing"
    - "two sided matching based cooperative spectrum sharing"
    - "economic analysis of crowdsourced wireless community networks"
    - "centurion incentivizing multi requester mobile crowd sensing"
    - "dynamic routing for social information sharing"
    - "providing long term participation incentive in participatory sensing"
    - "distributed time sensitive task selection in mobile crowdsensing"
    - "combining spot and futures markets a hybrid market approach to dynamic spectrum access"

Connected through hyperedge HE-2 (induced by source paper "near optimal and robust mechanism design for covering problems with correlated players"):
  with members:
    - "approximate revenue maximization with multiple items"
    - "reducing revenue to welfare maximization approximation algorithms and other generalizations"
    - "understanding incentives mechanism design becomes algorithm design"
    - "bayesian optimal auctions via multi to single agent reduction"
    - "optimal multi dimensional mechanism design reducing revenue to welfare maximization"
    - "optimal auctions with correlated bidders are easy"
    - "greedy facility location algorithms analyzed using dual fitting with factor revealing lp"

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)