human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "the generalized pignistic transformation"
  Abstract: This paper presents in detail the generalized pignistic transformation (GPT) succinctly developed in the Dezert-Smarandache Theory (DSmT) framework as a tool for decision process. The GPT allows to provide a subjective probability measure from any generalized basic belief assignment given by any corpus of evidence. We mainly focus our presentation on the 3D case and provide the complete result obtained by the GPT and its validation drawn from the probability theory.

Connected through hyperedge HE-1 (induced by source paper "implementing general belief function framework with a practical codification for low complexity"):
  with members:
    - "practical uses of belief functions"
    - "generalized proportional conflict redistribution rule applied to sonar imagery and radar targets classification"
    - "human expert fusion for image classification"
    - "a new generalization of the proportional conflict redistribution rule stable in terms of decision"
    - "decision support with belief functions theory for seabed characterization"
    - "a new probabilistic transformation of belief mass assignment"
    - "toward a combination rule to deal with partial conflict and specificity in belief functions theory"
    - "proportional conflict redistribution rules for information fusion"

Connected through hyperedge HE-2 (induced by source paper "a new generalization of the proportional conflict redistribution rule stable in terms of decision"):
  with members:
    - "adaptative combination rule and proportional conflict redistribution rule for information fusion"
    - "dsmt a new paradigm shift for information fusion"
    - "proportional conflict redistribution rules for information fusion"

Connected through hyperedge HE-3 (induced by source paper "generalized proportional conflict redistribution rule applied to sonar imagery and radar targets classification"):
  with members:
    - "human expert fusion for image classification"
    - "dsmt a new paradigm shift for information fusion"

Question: Please tell me which class the center node 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)