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: "artificial intelligence enabled software defined networking a comprehensive overview"
  Abstract: Software-defined networking (SDN) represents a promising networking architecture that combines central management and network programmability. SDN separates the control plane from the data plane and moves the network management to a central point, called the controller that can be programmed and used as the brain of the network. Recently, the research community has shown an increased tendency to benefit from the recent advancements in the artificial intelligence (AI) field to provide learning abilities and better decision making in SDN. In this study, the authors provide a detailed overview of the recent efforts to include AI in SDN. The study showed that the research efforts focused on three main sub-fields of AI namely: machine learning, meta-heuristics and fuzzy inference systems. Accordingly, in this work, the authors investigate their different application areas and potential use, as well as the improvements achieved by including AI-based techniques in the SDN paradigm.

Connected through hyperedge HE-1 (induced by source paper "a holistic survey of wireless multipath video streaming"):
  with members:
    - "network service orchestration a survey"
    - "the past present and future of transport layer multipath"
    - "distortion aware concurrent multipath transfer for mobile video streaming in heterogeneous wireless networks"
    - "bandwidth aggregation techniques in heterogeneous multi homed devices"
    - "exploiting the power of multiplicity a holistic survey of network layer multipath"
    - "a novel adaptation method for http streaming of vbr videos over mobile networks"
    - "software defined networking a comprehensive survey"

Connected through hyperedge HE-2 (induced by source paper "hymer a hybrid machine learning framework for energy efficient routing in sdn"):
  with members:
    - "resdn a novel metric and method for energy efficient routing in software defined networks"
    - "neuroute predictive dynamic routing for software defined networks"
    - "a deep reinforcement learning approach for software defined networking routing optimization"
    - "seer empowering software defined networking with data analytics"
    - "software defined networking a comprehensive survey"

Connected through hyperedge HE-3 (induced by source paper "when deep learning meets security"):
  with members:
    - "early stage malware prediction using recurrent neural networks"
    - "detecting malicious powershell commands using deep neural networks"
    - "deep neural networks for bot detection"
    - "iot security techniques based on machine learning"
    - "henet a deep learning approach on intel circledr processor trace for effective exploit detection"
    - "shallow and deep networks intrusion detection system a taxonomy and survey"
    - "expose a character level convolutional neural network with embeddings for detecting malicious urls file paths and registry keys"
    - "the rise of social bots"

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.AI(Artificial Intelligence)