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: "how much urban traffic is searching for parking"
  Abstract: In this paper we explore city-level traffic and parking data to determine how much cruising for curbside parking contributes to overall traffic congestion. To this end, we describe a new kind of queueing network and present a data-informed model based on this new queuing network. We leverage the data-informed model in developing and validating a simulation tool. In addition, we utilize curbside parking and arterial traffic volume data to produce an estimate of the proportion of traffic searching for parking along high occupancy arterials. Somewhat surprisingly, we find that while percentage increase in travel time to through traffic vehicles depends on time of day, it does not appear to depend on high volumes of through traffic. Moreover, we show that the probability of a block-face being full is a much more viable metric for directly controlling congestion than average occupancy rate, typically used by municipalities.

Connected through hyperedge HE-1 (induced by source paper "uncertainty in multi commodity routing networks when does it help"):
  with members:
    - "effects of information heterogeneity in bayesian routing games"
    - "informational braess paradox the effect of information on traffic congestion"
    - "to observe or not to observe queuing game framework for urban parking"
    - "power control in networks with heterogeneous users a quasi variational inequality approach"
    - "the burden of risk aversion in mean risk selfish routing"
    - "congestion games with distance based strict uncertainty"

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)