human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "theoretical formulation and analysis of the deterministic dendritic cell algorithm"):
  Abstract: As one of the emerging algorithms in the field of Artificial Immune Systems (AIS), the Dendritic Cell Algorithm (DCA) has been successfully applied to a number of challenging real-world problems. However, one criticism is the lack of a formal definition, which could result in ambiguity for understanding the algorithm. Moreover, previous investigations have mainly focused on its empirical aspects. Therefore, it is necessary to provide a formal definition of the algorithm, as well as to perform runtime analyses to revealits theoretical aspects. In this paper, we define the deterministic version of the DCA, named the dDCA, using set theory and mathematical functions. Runtime analyses of the standard algorithm and the one with additional segmentation are performed. Our analysis suggests that the standard dDCA has a runtime complexity of O(n2) for the worst-case scenario, where n is the number of input data instances. The introduction of segmentation changes the algorithm's worst case runtime complexity to O(max(nN; nz)), for DC population size N with size of each segment z. Finally, two runtime variables of the algorithm are formulated based on the input data, to understand its runtime behaviour as guidelines for further development.

Includes members:
  Member "the deterministic dendritic cell algorithm":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "quiet in class classification noise and the dendritic cell algorithm")
  Member "integrating real time analysis with the dendritic cell algorithm through segmentation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "the dendritic cell algorithm for intrusion detection")
  Member "further exploration of the dendritic cell algorithm antigen multiplier and time windows":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "negative selection approach application in network intrusion detection systems")
  Member "exploration of the dendritic cell algorithm using the duration calculus":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the dendritic cell algorithm for intrusion detection")
  Member "the application of a dendritic cell algorithm to a robotic classifier":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the dendritic cell algorithm for intrusion detection")
  Member "pca 4 dca the application of principal component analysis to the dendritic cell algorithm":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "the dendritic cell algorithm for intrusion detection")
  Member "dca for bot detection":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "the dendritic cell algorithm for intrusion detection")

Question: Please tell me which class the source paper 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.NE(Neural and Evolutionary Computing)