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 deterministic dendritic cell algorithm"
  Abstract: The Dendritic Cell Algorithm is an immune-inspired algorithm orig- inally based on the function of natural dendritic cells. The original instantiation of the algorithm is a highly stochastic algorithm. While the performance of the algorithm is good when applied to large real-time datasets, it is difficult to anal- yse due to the number of random-based elements. In this paper a deterministic version of the algorithm is proposed, implemented and tested using a port scan dataset to provide a controllable system. This version consists of a controllable amount of parameters, which are experimented with in this paper. In addition the effects are examined of the use of time windows and variation on the number of cells, both which are shown to influence the algorithm. Finally a novel metric for the assessment of the algorithms output is introduced and proves to be a more sensitive metric than the metric used with the original Dendritic Cell Algorithm.

Connected through hyperedge HE-1 (induced by source paper "theoretical formulation and analysis of the deterministic dendritic cell algorithm"):
  with members:
    - "integrating real time analysis with the dendritic cell algorithm through segmentation"
    - "further exploration of the dendritic cell algorithm antigen multiplier and time windows"
    - "exploration of the dendritic cell algorithm using the duration calculus"
    - "the application of a dendritic cell algorithm to a robotic classifier"
    - "pca 4 dca the application of principal component analysis to the dendritic cell algorithm"
    - "dca for bot detection"

Connected through hyperedge HE-2 (induced by source paper "quiet in class classification noise and the dendritic cell algorithm"):
  with members:
    - "behavioural correlation for detecting p2p bots"
    - "exploration of the dendritic cell algorithm using the duration calculus"

Connected through hyperedge HE-3 (induced by source paper "immuno inspired robotic applications a review"):
  with members:
    - "two timescale learning using idiotypic behaviour mediation for a navigating mobile robot"
    - "the application of a dendritic cell algorithm to a robotic classifier"
    - "an idiotypic immune network as a short term learning architecture for mobile robots"
    - "articulation and clarification of the dendritic cell algorithm"
    - "genetic algorithm seeding of idiotypic networks for mobile robot navigation"
    - "idiotypic immune networks in mobile robot control"

Connected through hyperedge HE-4 (induced by source paper "integrating real time analysis with the dendritic cell algorithm through segmentation"):
  with members:
    - "dendritic cells for syn scan detection"
    - "further exploration of the dendritic cell algorithm antigen multiplier and time windows"
    - "the application of a dendritic cell algorithm to a robotic classifier"
    - "dca for bot detection"

Connected through hyperedge HE-5 (induced by source paper "artificial dendritic cells multi faceted perspectives"):
  with members:
    - "further exploration of the dendritic cell algorithm antigen multiplier and time windows"
    - "the application of a dendritic cell algorithm to a robotic classifier"
    - "articulation and clarification of the dendritic cell algorithm"
    - "dca for bot detection"
    - "libtissue implementing innate immunity"

Connected through hyperedge HE-6 (induced by source paper "pca 4 dca the application of principal component analysis to the dendritic cell algorithm"):
  with members:
    - "integrating real time analysis with the dendritic cell algorithm through segmentation"
    - "further exploration of the dendritic cell algorithm antigen multiplier and time windows"

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)