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: "cim e oriented graph database model architecture and parallel network topology processing"
  Abstract: CIM/E is an easy and efficient electric power model exchange standard between different Energy Management System vendors. With the rapid growth of data size and system complexity, the traditional relational database is not the best option to store and process the data. In contrast, the graph database and graph computation show their potential advantages to handle the power system data and perform real-time data analytics and computation. The graph concept fits power grid data naturally because of the fundamental structure similarity. Vertex and edge in the graph database can act as both a parallel storage unit and a computation unit. In this paper, the CIM/E data is modeled into the graph database. Based on this model, the parallel network topology processing algorithm is established and conducted by applying graph computation. The modeling and parallel network topology processing have been demonstrated in the modified IEEE test cases and practical Sichuan power network. The processing efficiency is greatly improved using the proposed method.

Connected through hyperedge HE-1 (induced by source paper "graph computing based distributed state estimation with pmus"):
  with members:
    - "optimization of battery energy storage to improve power system oscillation damping"
    - "exploration of bi level pagerank algorithm for power flow analysis using graph database"
    - "exploration of graph computing in power system state estimation"

Connected through hyperedge HE-2 (induced by source paper "graph computing based distributed fast decoupled power flow analysis"):
  with members:
    - "graph based preconditioning conjugate gradient algorithm for n 1 contingency analysis"
    - "exploration of bi level pagerank algorithm for power flow analysis using graph database"
    - "exploration of graph computing in power system state estimation"

Connected through hyperedge HE-3 (induced by source paper "graph computing based fast screening in contingency analysis"):
  with members:
    - "graph based preconditioning conjugate gradient algorithm for n 1 contingency analysis"
    - "exploration of bi level pagerank algorithm for power flow analysis using graph database"
    - "exploration of graph computing in power system state estimation"

Connected through hyperedge HE-4 (induced by source paper "a high performance energy management system based on evolving graph"):
  with members:
    - "graph based preconditioning conjugate gradient algorithm for n 1 contingency analysis"
    - "exploration of graph computing in power system state estimation"

Connected through hyperedge HE-5 (induced by source paper "substation one line diagram automatic generation and visualization"):
  with members:
    - "graph based preconditioning conjugate gradient algorithm for n 1 contingency analysis"
    - "exploration of graph computing in power system state estimation"

Connected through hyperedge HE-6 (induced by source paper "exploration of bi level pagerank algorithm for power flow analysis using graph database"):
  with members:
    - "exploration of graph computing in power system state estimation"

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.DC(Distributed, Parallel, and Cluster Computing)