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: "a market for unbiased private data paying individuals according to their privacy attitudes"
  Abstract: Since there is, in principle, no reason why third parties should not pay individuals for the use of their data, we introduce a realistic market that would allow these payments to be made while taking into account the privacy attitude of the participants. And since it is usually important to use unbiased samples to obtain credible statistical results, we examine the properties that such a market should have and suggest a mechanism that compensates those individuals that participate according to their risk attitudes. Equally important, we show that this mechanism also benefits buyers, as they pay less for the data than they would if they compensated all individuals with the same maximum fee that the most concerned ones expect.

Connected through hyperedge HE-1 (induced by source paper "optimized direct sale of privacy in personal data marketplaces"):
  with members:
    - "myadchoices bringing transparency and control to online advertising"
    - "you never surf alone ubiquitous tracking of users browsing habits"
    - "a theory of pricing private data"
    - "conducting truthful surveys cheaply"
    - "take it or leave it running a survey when privacy comes at a cost"
    - "approximately optimal auctions for selling privacy when costs are correlated with data"
    - "privacy auctions for recommender systems"
    - "selling privacy at auction"

Connected through hyperedge HE-2 (induced by source paper "how to balance privacy and money through pricing mechanism in personal data market"):
  with members:
    - "differential privacy an economic method for choosing epsilon"
    - "a theory of pricing private data"
    - "approximately optimal auctions for selling privacy when costs are correlated with data"
    - "selling privacy at auction"

Connected through hyperedge HE-3 (induced by source paper "valorising the iot databox creating value for everyone"):
  with members:
    - "end to end privacy for open big data markets"
    - "big data privacy in the internet of things era"
    - "the emerging internet of things marketplace from an industrial perspective a survey"
    - "a survey on internet of things from industrial market perspective"
    - "improve the sustainability of internet of things through trading based value creation"
    - "human data interaction the human face of the data driven society"
    - "sensing as a service model for smart cities supported by internet of things"
    - "your browsing behavior for a big mac economics of personal information online"

Connected through hyperedge HE-4 (induced by source paper "differential privacy an economic method for choosing epsilon"):
  with members:
    - "a theory of pricing private data"
    - "calibrating data to sensitivity in private data analysis"
    - "conducting truthful surveys cheaply"
    - "privbasis frequent itemset mining with differential privacy"
    - "an adaptive mechanism for accurate query answering under differential privacy"
    - "privacy preserving record linkage via grams projections"
    - "take it or leave it running a survey when privacy comes at a cost"
    - "approximately optimal auctions for selling privacy when costs are correlated with data"

Connected through hyperedge HE-5 (induced by source paper "money walks a human centric study on the economics of personal mobile data"):
  with members:
    - "your browsing behavior for a big mac economics of personal information online"
    - "a refined experience sampling method to capture mobile user experience"

Connected through hyperedge HE-6 (induced by source paper "human data interaction the human face of the data driven society"):
  with members:
    - "privacy in sensor driven human data collection a guide for practitioners"
    - "sensing as a service and big data"

Connected through hyperedge HE-7 (induced by source paper "what s the gist privacy preserving aggregation of user profiles"):
  with members:
    - "your browsing behavior for a big mac economics of personal information online"

Connected through hyperedge HE-8 (induced by source paper "a theory of pricing private data"):
  with members:
    - "rappor randomized aggregatable privacy preserving ordinal response"
    - "redrawing the boundaries on purchasing data from privacy sensitive individuals"
    - "calibrating data to sensitivity in private data analysis"
    - "conducting truthful surveys cheaply"
    - "low rank mechanism for optimizing batch queries under differential privacy"
    - "take it or leave it running a survey when privacy comes at a cost"
    - "approximately optimal auctions for selling privacy when costs are correlated with data"
    - "truthful mechanisms for agents that value privacy"

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.CY(Computers and Society)