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: "dendritic cells for anomaly detection"
  Abstract: Artificial immune systems, more specifically the negative selection algorithm, have previously been applied to intrusion detection. The aim of this research is to develop an intrusion detection system based on a novel concept in immunology, the Danger Theory. Dendritic Cells (DCs) are antigen presenting cells and key to the activation of the human immune system. DCs perform the vital role of combining signals from the host tissue and correlate these signals with proteins known as antigens. In algorithmic terms, individual DCs perform multi-sensor data fusion based on time-windows. The whole population of DCs asynchronously correlates the fused signals with a secondary data stream. The behaviour of human DCs is abstracted to form the DC Algorithm (DCA), which is implemented using an immune inspired framework, libtissue. This system is used to detect context switching for a basic machine learning dataset and to detect outgoing portscans in real-time. Experimental results show a significant difference between an outgoing portscan and normal traffic.

Connected through hyperedge HE-1 (induced by source paper "probabilistic modeling for novelty detection with applications to fraud identification"):
  with members:
    - "a survey of parallel sequential pattern mining"
    - "a comparative evaluation of novelty detection algorithms for discrete sequences"
    - "visual interpretability for deep learning a survey"
    - "unsupervised anomaly detection with generative adversarial networks to guide marker discovery"
    - "neural autoregressive distribution estimation"
    - "distributed and parallel time series feature extraction for industrial big data applications"
    - "density estimation using real nvp"
    - "variational auto encoded deep gaussian processes"

Connected through hyperedge HE-2 (induced by source paper "a meta analysis of the anomaly detection problem"):
  with members:
    - "peak criterion for choosing gaussian kernel bandwidth in support vector data description"

Connected through hyperedge HE-3 (induced by source paper "systematic construction of anomaly detection benchmarks from real data"):
  with members:
    - "dendritic cells for syn scan detection"

Connected through hyperedge HE-4 (induced by source paper "information fusion for anomaly detection with the dendritic cell algorithm"):
  with members:
    - "introducing dendritic cells as a novel immune inspired algorithm for anomoly detection"
    - "towards a conceptual framework for innate immunity"
    - "articulation and clarification of the dendritic cell algorithm"
    - "libtissue implementing innate immunity"

Connected through hyperedge HE-5 (induced by source paper "information fusion in the immune system"):
  with members:
    - "articulation and clarification of the dendritic cell algorithm"
    - "an immune inspired approach to anomaly detection"
    - "immune system approaches to intrusion detection a review"
    - "libtissue implementing innate immunity"

Connected through hyperedge HE-6 (induced by source paper "the deterministic dendritic cell algorithm"):
  with members:
    - "information fusion for anomaly detection with the dendritic cell algorithm"
    - "the application of a dendritic cell algorithm to a robotic classifier"
    - "articulation and clarification of the dendritic cell algorithm"

Connected through hyperedge HE-7 (induced by source paper "detecting anomalous process behaviour using second generation artificial immune systems"):
  with members:
    - "towards a conceptual framework for innate immunity"
    - "articulation and clarification of the dendritic cell algorithm"
    - "libtissue implementing innate immunity"

Connected through hyperedge HE-8 (induced by source paper "dendritic cells for syn scan detection"):
  with members:
    - "articulation and clarification of the dendritic cell algorithm"
    - "libtissue implementing innate immunity"

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)