human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "a comparison of non intrusive load monitoring methods for commercial and residential buildings"):
  Abstract: Non intrusive load monitoring (NILM), or energy disaggregation, is the process of separating the total electricity consumption of a building as measured at single point into the building’s constituent loads. Previous research in the eld has mostly focused on residential buildings, and although the potential benets of applying this technology to commercial buildings have been recognised since the eld’s conception, NILM in the commercial domain has been largely unexplored by the academic community. As a result of the heterogeneity of this section of the building stock (i.e., encompassing buildings as diverse as airports, malls and coee shops), and hence the loads within them, many of the solutions developed for residential energy disaggregation do not apply directly. In this paper we highlight some insights for NILM in the commercial domain using data collected from a large smart meter deployment within an educational campus in Delhi, India, of which a subset of the data has been released for public use. We present an empirical characterisation of loads in commercial buildings, highlighting the dierences in energy consumption and load characteristics between residential and commercial buildings. We assess the validity of the assumptions generally made by NILM solutions for residential buildings when applied to measurements from commercial facilities. Based on our observations, we discuss the required traits for a NILM system for commercial buildings, and run benchmark residential NILM algorithms on our data set to conrm our observations. To advance the research in commercial buildings energy disaggregation, we release a subset of our data set, called COMBED (commercial building energy data set).

Includes members:
  Member "greend an energy consumption dataset of households in italy and austria":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a survey on non intrusive load monitoring methodies and techniques for energy disaggregation problem")
  Member "an in depth study into using emi signatures for appliance identification":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "beyond control enabling smart thermostats for leakage detection")
  Member "data driven energy efficiency in buildings":
    also connected through other hyperedges:
      (none)
  Member "metadata for energy disaggregation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "an open solution to provide personalized feedback for building energy management")

Question: Please tell me which class the source paper 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.SY(Systems and Control)