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: "metadata for energy disaggregation"
  Abstract: Energy disaggregation is the process of estimating the energy consumed by individual electrical appliances given only a time series of the whole-home power demand. Energy disaggregation researchers require datasets of the power demand from individual appliances and the whole-home power demand. Multiple such datasets have been released over the last few years but provide metadata in a disparate array of formats including CSV files and plain-text README files. At best, the lack of a standard metadata schema makes it unnecessarily time-consuming to write software to process multiple datasets and, at worse, the lack of a standard means that crucial information is simply absent from some datasets. We propose a metadata schema for representing appliances, meters, buildings, datasets, prior knowledge about appliances and appliance models. The schema is relational and provides a simple but powerful inheritance mechanism.

Connected through hyperedge HE-1 (induced by source paper "an open solution to provide personalized feedback for building energy management"):
  with members:
    - "greend an energy consumption dataset of households in italy and austria"
    - "yomo the arduino based smart metering board"

Connected through hyperedge HE-2 (induced by source paper "the uk dale dataset domestic appliance level electricity demand and whole house demand from five uk homes"):
  with members:
    - "greend an energy consumption dataset of households in italy and austria"
    - "a comparison of non intrusive load monitoring methods for commercial and residential buildings"

Connected through hyperedge HE-3 (induced by source paper "a comparison of non intrusive load monitoring methods for commercial and residential buildings"):
  with members:
    - "greend an energy consumption dataset of households in italy and austria"
    - "an in depth study into using emi signatures for appliance identification"
    - "data driven energy efficiency in buildings"

Connected through hyperedge HE-4 (induced by source paper "nilmtk v0 2 a non intrusive load monitoring toolkit for large scale data sets demo abstract"):
  with members:
    - "the uk dale dataset domestic appliance level electricity demand and whole house demand from five uk homes"
    - "greend an energy consumption dataset of households in italy and austria"
    - "a comparison of non intrusive load monitoring methods for commercial and residential buildings"

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)