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: "the computing of digital ecosystems"
  Abstract: A primary motivation for our research in digital ecosystems is the desire to exploit the self-organising properties of biological ecosystems. Ecosystems are thought to be robust, scalable architectures that can automatically solve complex, dynamic problems. However, the computing technologies that contribute to these properties have not been made explicit in digital ecosystems research. Here, we discuss how different computing technologies can contribute to providing the necessary self-organising features, including Multi-Agent Systems (MASs), Service-Oriented Architectures (SOAs), and distributed evolutionary computing (DEC). The potential for exploiting these properties in digital ecosystems is considered, suggesting how several key features of biological ecosystems can be exploited in Digital Ecosystems, and discussing how mimicking these features may assist in developing robust, scalable self-organising architectures. An example architecture, the Digital Ecosystem, is considered in detail. The Digital Ecosystem is then measured experimentally through simulations, considering the self-organised diversity of its evolving agent populations relative to the user request behaviour.

Connected through hyperedge HE-1 (induced by source paper "ecosystem oriented distributed evolutionary computing"):
  with members:
    - "self organisation of evolving agent populations in digital ecosystems"
    - "stability of evolving multiagent systems"
    - "digital ecosystems ecosystem oriented architectures"
    - "complex adaptive digital ecosystems"
    - "the abc of digital business ecosystems"
    - "digital ecosystems self organisation of evolving agent populations"
    - "digital ecosystems stability of evolving agent populations"
    - "biology of applied digital ecosystems"

Connected through hyperedge HE-2 (induced by source paper "self organisation of evolving agent populations in digital ecosystems"):
  with members:
    - "complex adaptive digital ecosystems"
    - "the abc of digital business ecosystems"
    - "digital ecosystems self organisation of evolving agent populations"
    - "scalability and optimisation of a committee of agents using genetic algorithm"
    - "digital ecosystems stability of evolving agent populations"
    - "biology of applied digital ecosystems"
    - "digital ecosystems optimisation by a distributed intelligence"
    - "digital ecosystems evolving service oriented architectures"

Connected through hyperedge HE-3 (induced by source paper "digital ecosystems ecosystem oriented architectures"):
  with members:
    - "complex adaptive digital ecosystems"
    - "the abc of digital business ecosystems"
    - "digital business ecosystems natural science paradigms"
    - "digital ecosystems self organisation of evolving agent populations"
    - "biology of applied digital ecosystems"
    - "digital ecosystems evolving service oriented architectures"
    - "avoiding the bloat with stochastic grammar based genetic programming"

Connected through hyperedge HE-4 (induced by source paper "stability of evolving multiagent systems"):
  with members:
    - "complex adaptive digital ecosystems"
    - "the abc of digital business ecosystems"
    - "digital ecosystems self organisation of evolving agent populations"
    - "scalability and optimisation of a committee of agents using genetic algorithm"
    - "digital ecosystems stability of evolving agent populations"
    - "biology of applied digital ecosystems"

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)