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 "implementing general belief function framework with a practical codification for low complexity"):
  Abstract: In this chapter, we propose a new practical codification of the elements of the Venn diagram in order to easily manipulate the focal elements. In order to reduce the complexity, the eventual constraints must be integrated in the codification at the beginning. Hence, we only consider a reduced hyper power set $D_r^\Theta$ that can be $2^\Theta$ or $D^\Theta$. We describe all the steps of a general belief function framework. The step of decision is particularly studied, indeed, when we can decide on intersections of the singletons of the discernment space no actual decision functions are easily to use. Hence, two approaches are proposed, an extension of previous one and an approach based on the specificity of the elements on which to decide. The principal goal of this chapter is to provide practical codes of a general belief function framework for the researchers and users needing the belief function 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 "generalized proportional conflict redistribution rule applied to sonar imagery and radar targets classification":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "fusion of qualitative beliefs using dsmt")
  Member "human expert fusion for image classification":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "conflict management in information fusion with belief functions")
  Member "a new generalization of the proportional conflict redistribution rule stable in terms of decision":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a two step fusion process for multi criteria decision applied to natural hazards in mountains")
  Member "decision support with belief functions theory for seabed characterization":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "conflict management in information fusion with belief functions")
  Member "a new probabilistic transformation of belief mass assignment":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "d numbers theory a generalization of dempster shafer theory")
  Member "toward a combination rule to deal with partial conflict and specificity in belief functions theory":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "idcr improved dempster combination rule for multisensor fault diagnosis")
  Member "proportional conflict redistribution rules for information fusion":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "idcr improved dempster combination rule for multisensor fault diagnosis")

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)