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 "an approach to characterize graded entailment of arguments through a label based framework"):
  Abstract: Argumentation theory is a powerful paradigm that formalizes a type of commonsense reasoning that aims to simulate the human ability to resolve a specific problem in an intelligent manner. A classical argumentation process takes into account only the properties related to the intrinsic logical soundness of an argument in order to determine its acceptability status. However, these properties are not always the only ones that matter to establish the argument's acceptabilitythere exist other qualities, such as strength, weight, social votes, trust degree, relevance level, and certainty degree, among others.In this work, we redefine the argumentative process to improve the analysis of arguments by considering their special features in order to obtain more refined results. Towards this end, we propose adding meta-level information to the arguments in the form of labels representing quantifiable data ranking over a range of fuzzy valuations. These labels are propagated through an argumentative graph according to the relations of support, conflict, and aggregation between arguments. Through this process we obtain final labels that are useful in determining argument acceptability. We redefine the argumentative process improving the argumentation analysis considering special features of the arguments.We add meta-level information to arguments as labels representing quantifiable data ranking over a fuzzy valuations range.Labels are propagated through an argumentative graph according to the relations of support, conflict, and aggregation.Label information is used to establish the arguments' acceptability according to different acceptance levels.We define an acceptability threshold to determine whether an argument satisfies certain conditions to be accepted.

Includes members:
  Member "on the acceptability of arguments in preference based argumentation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "an implementation empirical evaluation and proposed improvement for bidirectional splitting method for argumentation frameworks under stable semantics")
  Member "a logic programming framework for possibilistic argumentation with vague knowledge":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "belief revision in structured probabilistic argumentation")
  Member "graduality in argumentation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "broadening label based argumentation semantics with may must scales")
  Member "value based argumentation frameworks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "enumeration of preferred extensions in almost oriented digraphs")

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)