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 "fast dempster shafer clustering using a neural network structure"):
  Abstract: In this article we study a problem within Dempster-Shafer theory where 2 n — 1 pieces of evidence are clustered by a neural structure into n clusters. The clustering is done by minimizing a metaconflict function. Previously we developed a method based on iterative optimization. However, for large scale problems we need a method with lower computational complexity. The neural structure was found to be effective and much faster than iterative optimization for larger problems. While the growth in metaconflict was faster for the neural structure compared with iterative optimization in medium sized problems, the metaconflict per cluster and evidence was moderate. The neural structure was able to find a global minimum over ten runs for problem sizes up to six clusters.

Includes members:
  Member "dempster s rule for evidence ordered in a complete directed acyclic graph":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "finding a posterior domain probability distribution by specifying nonspecific evidence")
  Member "finding a posterior domain probability distribution by specifying nonspecific evidence":
    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 "simultaneous dempster shafer clustering and gradual determination of number of clusters 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 "simultaneous dempster shafer clustering and gradual determination of number of clusters 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)