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 "theseus incentivizing truth discovery in mobile crowd sensing systems"):
  Abstract: The recent proliferation of human-carried mobile devices has given rise to mobile crowd sensing (MCS) systems that outsource sensory data collection to the public crowd. In order to identify truthful values from (crowd) workers' noisy or even conflicting sensory data, truth discovery algorithms, which jointly estimate workers' data quality and the underlying truths through quality-aware data aggregation, have drawn significant attention. However, the power of these algorithms could not be fully unleashed in MCS systems, unless workers' strategic reduction of their sensing effort is properly tackled. To address this issue, in this paper, we propose a payment mechanism, named Theseus, that deals with workers' such strategic behavior, and incentivizes high-effort sensing from workers. We ensure that, at the Bayesian Nash Equilibrium of the non-cooperative game induced by Theseus, all participating workers will spend their maximum possible effort on sensing, which improves their data quality. As a result, the aggregated results calculated subsequently by truth discovery algorithms based on workers' data will be highly accurate. Additionally, Theseus bears other desirable properties, including individual rationality and budget feasibility. We validate the desirable properties of Theseus through theoretical analysis, as well as extensive simulations.

Includes members:
  Member "centurion incentivizing multi requester mobile crowd sensing":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "multimedia crowdsourcing with bounded rationality a cognitive hierarchy perspective")
  Member "the value of privacy strategic data subjects incentive mechanisms and fundamental limits":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "prospect theoretic analysis of privacy preserving mechanism")
  Member "providing long term participation incentive in participatory sensing":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "small profits and quick returns an incentive mechanism design for iot based crowdsourcing under continuous platform competition")
  Member "crowdsourcing with tullock contests a new perspective":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "small profits and quick returns an incentive mechanism design for iot based crowdsourcing under continuous platform competition")
  Member "truthful linear regression":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "causal feature discovery through strategic modification")
  Member "distributed time sensitive task selection in mobile crowdsensing":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "trajectory design for multiple uav assisted wireless networks")
  Member "linear regression as a non cooperative game":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "causal feature discovery through strategic modification")

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)