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 symbolic approach to reasoning with linguistic quantifiers"
  Abstract: This paper investigates the possibility of performing automated reasoning in probabilistic logic when probabilities are expressed by means of linguistic quantifiers. Each linguistic term is expressed as a prescribed interval of proportions. Then instead of propagating numbers, qualitative terms are propagated in accordance with the numerical interpretation of these terms. The quantified syllogism, modelling the chaining of probabilistic rules, is studied in this context. It is shown that a qualitative counterpart of this syllogism makes sense, and is relatively independent of the threshold defining the linguistically meaningful intervals, provided that these threshold values remain in accordance with the intuition. The inference power is less than that of a full-fledged probabilistic con-quaint propagation device but better corresponds to what could be thought of as commonsense probabilistic reasoning.

Connected through hyperedge HE-1 (induced by source paper "refining reasoning in qualitative probabilistic networks"):
  with members:
    - "on reasoning in networks with qualitative uncertainty"
    - "argumentative inference in uncertain and inconsistent knowledge bases"
    - "argument calculus and networks"
    - "an experimental comparison of numerical and qualitative probabilistic reasoning"

Connected through hyperedge HE-2 (induced by source paper "magic inference rules for probabilistic deduction under taxonomic knowledge"):
  with members:
    - "constraint propagation with imprecise conditional probabilities"
    - "probabilistic description logics"
    - "probabilistic deduction with conditional constraints over basic events"

Connected through hyperedge HE-3 (induced by source paper "probabilistic description logics"):
  with members:
    - "towards precision of probabilistic bounds propagation"

Connected through hyperedge HE-4 (induced by source paper "fusion of qualitative beliefs using dsmt"):
  with members:
    - "generalized proportional conflict redistribution rule applied to sonar imagery and radar targets classification"
    - "target type tracking with pcr5 and dempster s rules a comparative analysis"
    - "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)