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 "simultaneous dempster shafer clustering and gradual determination of number of clusters using a neural network structure"):
  Abstract: Extends an earlier result (Johan, 1998) within Dempster-Shafer theory where several pieces of evidence were clustered into a fixed number of clusters using a neural structure. This was done by minimizing a metaconflict function. We now develop a method for simultaneous clustering and determination of number of clusters during iteration in the neural structure. We let the output signals of neurons represent the degree to which pieces of evidence belong to a corresponding cluster. From these we derive a probability distribution regarding the number of clusters, which gradually during the iteration is transformed into a determination of number of clusters. This gradual determination is fed back into the neural structure at each iteration to influence the clustering process.

Includes members:
  Member "finding a posterior domain probability distribution by specifying nonspecific evidence":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "managing inconsistent intelligence")
  Member "a neural network and iterative optimization hybrid for dempster shafer clustering":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "managing inconsistent intelligence")
  Member "applying data mining and machine learning techniques to submarine intelligence analysis":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "fast dempster shafer clustering using a neural network structure")
  Member "on nonspecific evidence":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "managing inconsistent intelligence")
  Member "creating prototypes for fast classification in dempster shafer clustering":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "managing inconsistent intelligence")
  Member "cluster based specification techniques in dempster shafer theory":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "practical uses of belief functions")
  Member "specifying nonspecific evidence":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "managing inconsistent intelligence")
  Member "fast dempster shafer clustering using a neural network structure":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "managing inconsistent intelligence")

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.AI(Artificial Intelligence)