human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "privacy preserving verifiable incentive mechanism for crowdsourcing market applications"):
  Abstract: Recently, a novel class of incentive mechanisms is proposed to attract extensive users to truthfully participate in crowd sensing applications with a given budget constraint. The class mechanisms also bring good service quality for the requesters in crowd sensing applications. Although it is so important, there still exists many verification and privacy challenges, including users' bids and subtask information privacy and identification privacy, winners' set privacy of the platform, and the security of the payment outcomes. In this paper, we present a privacy-preserving verifiable incentive mechanism for crowd sensing applications with the budget constraint, not only to explore how to protect the privacies of users and the platform, but also to make the verifiable payment correct between the platform and users for crowd sensing applications. Results indicate that our privacy-preserving verifiable incentive mechanism achieves the same results as the generic one without privacy preservation.

Includes members:
  Member "enabling privacy preserving auctions in big data":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "general privacy preserving verifiable incentive mechanism for crowdsourcing markets")
  Member "from convex optimization to randomized mechanisms toward optimal combinatorial auctions":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "improved truthful mechanisms for combinatorial auctions with submodular bidders")
  Member "budget feasible mechanisms":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "budget feasible mechanism design for non monotone submodular objectives offline and online")

Question: Please tell me which class the source paper 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)