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: "creating a surrogate commuter network from australian bureau of statistics census data"
  Abstract: Between the 2011 and 2016 national censuses, the Australian Bureau of Statistics changed its anonymity policy compliance system for the distribution of census data. This change has resulted in a lack of consistency over the different partition resolutions that define the sizes of local populations. Here, we address this inconsistency with respect to the 2016 usual-residence to place-of-work travel data. The lack of consistency manifests in several ways that can dramatically influence the mobility network derived from this data. For example, it introduces a strong correlation between the total number of commuters accounted for in the database and the size of the population partition used to create the network. This results in up to ~30% of the working population disappearing for the highest-resolution partition scheme. Here, we introduce a re-sampling system that rectifies many of these artifacts, ensuring a higher level of consistency in the derived mobility network across partition sizes. We offer a surrogate high-resolution 2016 commuter database that reduces the discrepancy between commuter totals from ~30% to only ~7%, which is on the order of the discrepancy introduced by the privacy policy compliance system used in earlier years.

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.DB(Databases)