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: "incentive mechanisms for participatory sensing survey and research challenges"
  Abstract: Participatory sensing is a powerful paradigm which takes advantage of smartphones to collect and analyze data beyond the scale of what was previously possible. Given that participatory sensing systems rely completely on the users' willingness to submit up-to-date and accurate information, it is paramount to effectively incentivize users' active and reliable participation. In this paper, we survey existing literature on incentive mechanisms for participatory sensing systems. In particular, we present a taxonomy of existing incentive mechanisms for participatory sensing systems, which are subsequently discussed in depth by comparing and contrasting different approaches. Finally, we discuss an agenda of open research challenges in incentivizing users in participatory sensing.

Connected through hyperedge HE-1 (induced by source paper "a novel methodology for designing policies in mobile crowdsensing systems"):
  with members:
    - "incentme effective mechanism design to stimulate crowdsensing participants with uncertain mobility"
    - "quality of information in mobile crowdsensing survey and research challenges"
    - "a socially aware incentive mechanism for mobile crowdsensing service market"

Connected through hyperedge HE-2 (induced by source paper "task allocation and mobile base station deployment in wireless powered spatial crowdsourcing"):
  with members:
    - "wireless powered communication opportunities and challenges"
    - "wireless information and power transfer architecture design and rate energy tradeoff"

Connected through hyperedge HE-3 (induced by source paper "securing the internet of things in the age of machine learning and software defined networking"):
  with members:
    - "quality of information in mobile crowdsensing survey and research challenges"
    - "learning to detect and mitigate cross layer attacks in wireless networks framework and applications"
    - "iot sentinel demo automated device type identification for security enforcement in iot"
    - "low power wide area networks an overview"
    - "a survey on wireless security technical challenges recent advances and future trends"
    - "understanding modern banking ledgers through blockchain technologies future of transaction processing and smart contracts on the internet of money"
    - "device fingerprinting in wireless networks challenges and opportunities"
    - "a survey on truth discovery"

Connected through hyperedge HE-4 (induced by source paper "incentme effective mechanism design to stimulate crowdsensing participants with uncertain mobility"):
  with members:
    - "securing the internet of things in the age of machine learning and software defined networking"
    - "quality of information in mobile crowdsensing survey and research challenges"
    - "taskme multi task allocation in mobile crowd sensing"
    - "mining users significant driving routes with low power sensors"
    - "on the approximability of budget feasible mechanisms"
    - "budget feasible mechanisms"

Connected through hyperedge HE-5 (induced by source paper "station assignment with reallocation"):
  with members:
    - "a new perspective on the windows scheduling problem"
    - "dynamic windows scheduling with reallocation"
    - "reallocation problems in scheduling"
    - "online primal dual for non linear optimization with applications to speed scaling"
    - "on the value of job migration in online makespan minimization"
    - "online stochastic matching beating 1 1 e"

Connected through hyperedge HE-6 (induced by source paper "ps sim a framework for scalable simulation of participatory sensing data"):
  with members:
    - "providing long term participation incentive in participatory sensing"

Connected through hyperedge HE-7 (induced by source paper "quality of information in mobile crowdsensing survey and research challenges"):
  with members:
    - "centurion incentivizing multi requester mobile crowd sensing"
    - "taskme multi task allocation in mobile crowd sensing"
    - "sacrm social aware crowdsourcing with reputation management in mobile sensing"
    - "a survey on truth discovery"
    - "mining users significant driving routes with low power sensors"
    - "ear phone a context aware noise mapping using smart phones"
    - "a trust based recruitment framework for multi hop social participatory sensing"
    - "a bayesian approach to discovering truth from conflicting sources for data integration"

Connected through hyperedge HE-8 (induced by source paper "online participatory sensing in double auction environment with location information"):
  with members:
    - "quality adaptive online double auction in participatory sensing"
    - "participatory privacy enabling privacy in participatory sensing"
    - "models for truthful online double auctions"

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)