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: "a new generalization of the proportional conflict redistribution rule stable in terms of decision"
  Abstract: In this chapter, we present and discuss a new generalized proportional conflict redistribution rule. The Dezert-Smarandache extension of the Demster-Shafer theory has relaunched the studies on the combination rules especially for the management of the conflict. Many combination rules have been proposed in the last few years. We study here different combination rules and compare them in terms of decision on didactic example and on generated data. Indeed, in real applications, we need a reliable decision and it is the final results that matter. This chapter shows that a fine proportional conflict redistribution rule must be preferred for the combination in the belief function theory.

Connected through hyperedge HE-1 (induced by source paper "a two step fusion process for multi criteria decision applied to natural hazards in mountains"):
  with members:
    - "an introduction to dsmt"
    - "implementing general belief function framework with a practical codification for low complexity"
    - "proportional conflict redistribution rules for information fusion"

Connected through hyperedge HE-2 (induced by source paper "threat assessment of a possible vehicle born improvised explosive device using dsmt"):
  with members:
    - "implementing general belief function framework with a practical codification for low complexity"

Connected through hyperedge HE-3 (induced by source paper "general combination rules for qualitative and quantitative beliefs"):
  with members:
    - "toward a combination rule to deal with partial conflict and specificity in belief functions theory"
    - "qualitative belief conditioning rules qbcr"
    - "adaptative combination rule and proportional conflict redistribution rule for information fusion"
    - "proportional conflict redistribution rules for information fusion"

Connected through hyperedge HE-4 (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"
    - "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"
    - "the generalized pignistic transformation"

Connected through hyperedge HE-5 (induced by source paper "toward a combination rule to deal with partial conflict and specificity in belief functions theory"):
  with members:
    - "adaptative combination rule and proportional conflict redistribution rule for information fusion"
    - "proportional conflict redistribution rules for information fusion"

Connected through hyperedge HE-6 (induced by source paper "target type tracking with pcr5 and dempster s rules a comparative analysis"):
  with members:
    - "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)