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 "reliable force aggregation using a refined evidence specification from dempster shafer clustering"):
  Abstract: In this paper we develop methods for selection of templates and use these templates to recluster an already performed Dempster-Shafer clustering taking into account intelligence to template fit during the reclustering phase. By this process the risk of erroneous force aggregation based on some misplace pieces of evidence from the first clustering process is greatly reduced. Finally, a more reliable force aggregation is performed using the result of the second clustering. These steps are taken in order to maintain most of the excellent computational performance of Dempster-Shafer clustering, while at the same time improve on the clustering result by including some higher relations among intelligence reports described by the templates. The new improved algorithm has a computational complexity of O(n**3 log**2 n) compared to O(n**2 log**2 n) of standard Dempster-Shafer clustering using Potts spin mean field theory.

Includes members:
  Member "practical uses of belief functions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "evidence updating for stream processing in big data robust conditioning in soft and hard fusion environments")
  Member "on nonspecific evidence":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "managing inconsistent intelligence")
  Member "managing inconsistent intelligence":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "robust report level cluster to track fusion")
  Member "dempster shafer clustering using potts spin mean field theory":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "extremal optimization for sensor report pre processing")
  Member "specifying nonspecific evidence":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "managing inconsistent intelligence")
  Member "fast dempster shafer clustering using a neural network structure":
    also connected through other hyperedges:
      - Hyperedge HE-6 (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-7 (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)