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 correspondence analysis platform for uncovering deep structure in data and information"
  Abstract: We study two aspects of information semantics: (i) the collection of all relationships, (ii) tracking and spotting anomaly and change. The first is implemented by endowing all relevant information spaces with a Euclidean metric in a common projected space. The second is modelled by an induced ultrametric. A very general way to achieve a Euclidean embedding of different information spaces based on cross-tabulation counts (and from other input data formats) is provided by correspondence analysis. From there, the induced ultrametric that we are particularly interested in takes a sequential—e.g. temporal—ordering of the data into account. We employ such a perspective to look at narrative, ‘the flow of thought and the flow of language’ (Chafe). In application to policy decision making, we show how we can focus analysis in a small number of dimensions.

Connected through hyperedge HE-1 (induced by source paper "qualitative judgement of research impact domain taxonomy as a fundamental framework for judgement of the quality of research"):
  with members:
    - "identification of influential scientists vs mass producers by the perfectionism index"
    - "a measure for the impact of research"
    - "national peer review research assessment exercises for the hard sciences can be a complete waste of money the italian case"

Connected through hyperedge HE-2 (induced by source paper "the geometry and topology of data and information for analytics of processes and behaviours building on bourdieu and addressing new societal challenges"):
  with members:
    - "contextualizing geometric data analysis and related data analytics a virtual microscope for big data analytics"
    - "sparse p adic data coding for computationally efficient and effective big data analytics"
    - "computational properties of fiction writing and collaborative work"
    - "the structure of narrative the case of film scripts"

Connected through hyperedge HE-3 (induced by source paper "contextualizing geometric data analysis and related data analytics a virtual microscope for big data analytics"):
  with members:
    - "qualitative judgement of research impact domain taxonomy as a fundamental framework for judgement of the quality of research"
    - "the geometry and topology of data and information for analytics of processes and behaviours building on bourdieu and addressing new societal challenges"

Connected through hyperedge HE-4 (induced by source paper "ultrametric model of mind i review"):
  with members:
    - "ultrametric model of mind ii application to text content analysis"
    - "on ultrametric algorithmic information"
    - "the structure of narrative the case of film scripts"

Connected through hyperedge HE-5 (induced by source paper "tag clouds for displaying semantics the case of filmscripts"):
  with members:
    - "the structure of narrative the case of film scripts"
    - "tag cloud drawing algorithms for cloud visualization"

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)