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: "reputation based incentive protocols in crowdsourcing applications"
  Abstract: Crowdsourcing websites (e.g. Yahoo! Answers, Amazon Mechanical Turk, and etc.) emerged in recent years that allow requesters from all around the world to post tasks and seek help from an equally global pool of workers. However, intrinsic incentive problems reside in crowdsourcing applications as workers and requester are selfish and aim to strategically maximize their own benefit. In this paper, we propose to provide incentives for workers to exert effort using a novel game-theoretic model based on repeated games. As there is always a gap in the social welfare between the non-cooperative equilibria emerging when workers pursue their self-interests and the desirable Pareto efficient outcome, we propose a novel class of incentive protocols based on social norms which integrates reputation mechanisms into the existing pricing schemes currently implemented on crowdsourcing websites, in order to improve the performance of the non-cooperative equilibria emerging in such applications. We first formulate the exchanges on a crowdsourcing website as a two-sided market where requesters and workers are matched and play gift-giving games repeatedly. Subsequently, we study the protocol designer's problem of finding an optimal and sustainable (equilibrium) protocol which achieves the highest social welfare for that website. We prove that the proposed incentives protocol can make the website operate close to Pareto efficiency. Moreover, we also examine an alternative scenario, where the protocol designer aims at maximizing the revenue of the website and evaluate the performance of the optimal protocol.

Connected through hyperedge HE-1 (induced by source paper "prospect theory based crowdsourcing for classification in the presence of spammers"):
  with members:
    - "decision tree design for classification in crowdsourcing systems"
    - "optimal crowdsourced classification with a reject option in the presence of spammers"
    - "does confidence reporting from the crowd benefit crowdsourcing performance"
    - "multi object classification via crowdsourcing with a reject option"
    - "double or nothing multiplicative incentive mechanisms for crowdsourcing"
    - "reliable crowdsourcing for multi class labeling using coding theory"
    - "serf and turf crowdturfing for fun and profit"

Connected through hyperedge HE-2 (induced by source paper "multimedia crowdsourcing with bounded rationality a cognitive hierarchy perspective"):
  with members:
    - "cognitive hierarchy theory for distributed resource allocation in the internet of things"
    - "centurion incentivizing multi requester mobile crowd sensing"

Connected through hyperedge HE-3 (induced by source paper "on the posted pricing in crowdsourcing power of bonus"):
  with members:
    - "optimal posted prices for online cloud resource allocation"
    - "bayesian budget feasibility with posted pricing"
    - "approval voting and incentives in crowdsourcing"
    - "incentivizing high quality crowdwork"
    - "mechanism design for crowdsourcing an optimal 1 1 e competitive budget feasible mechanism for large markets"
    - "double or nothing multiplicative incentive mechanisms for crowdsourcing"
    - "truelabel confusions a spectrum of probabilistic models in analyzing multiple ratings"
    - "optimal crowdsourcing contests"

Connected through hyperedge HE-4 (induced by source paper "zebralancer crowdsource knowledge atop open blockchain privately and anonymously"):
  with members:
    - "sentiment protocol a decentralized protocol leveraging crowd sourced wisdom"
    - "enigma decentralized computation platform with guaranteed privacy"
    - "double or nothing multiplicative incentive mechanisms for crowdsourcing"

Connected through hyperedge HE-5 (induced by source paper "zebralancer private and anonymous crowdsourcing system atop open blockchain"):
  with members:
    - "sentiment protocol a decentralized protocol leveraging crowd sourced wisdom"
    - "enigma decentralized computation platform with guaranteed privacy"
    - "double or nothing multiplicative incentive mechanisms for crowdsourcing"

Connected through hyperedge HE-6 (induced by source paper "rating protocol design for extortion and cooperation in the crowdsourcing contest dilemma"):
  with members:
    - "when reputation enforces evolutionary cooperation in unreliable manets"
    - "optimal prizes for all pay contests in heterogeneous crowdsourcing"
    - "iterated crowdsourcing dilemma game"
    - "socially optimal design of service exchange platforms with imperfect monitoring"
    - "medium access control protocols with memory"

Connected through hyperedge HE-7 (induced by source paper "does confidence reporting from the crowd benefit crowdsourcing performance"):
  with members:
    - "multi object classification via crowdsourcing with a reject option"
    - "double or nothing multiplicative incentive mechanisms for crowdsourcing"
    - "reliable crowdsourcing for multi class labeling using coding theory"

Connected through hyperedge HE-8 (induced by source paper "multi object classification via crowdsourcing with a reject option"):
  with members:
    - "reliable crowdsourcing for multi class labeling using coding theory"

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.AI(Artificial Intelligence)