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: "computing as information compression by multiple alignment unification and search"
  Abstract: This paper argues that the operations of a 'Universal Turing Machine' (UTM) and equivalent mechanisms such as the 'Post Canonical System' (PCS) - which are widely accepted as definitions of the concept of `computing' - may be interpreted as *information compression by multiple alignment, unification and search* (ICMAUS). #R##N#The motivation for this interpretation is that it suggests ways in which the UTM/PCS model may be augmented in a proposed new computing system designed to exploit the ICMAUS principles as fully as possible. The provision of a relatively sophisticated search mechanism in the proposed 'SP' system appears to open the door to the integration and simplification of a range of functions including unsupervised inductive learning, best-match pattern recognition and information retrieval, probabilistic reasoning, planning and problem solving, and others. Detailed consideration of how the ICMAUS principles may be applied to these functions is outside the scope of this article but relevant sources are cited in this article.

Connected through hyperedge HE-1 (induced by source paper "towards an intelligent database system founded on the sp theory of computing and cognition"):
  with members:
    - "unifying computing and cognition the sp theory and its applications"
    - "syntax parsing and production of natural language in a framework of information compression by multiple alignment unification and search"
    - "probabilistic reasoning as information compression by multiple alignment unification and search an introduction and overview"
    - "unsupervised grammar induction in a framework of information compression by multiple alignment unification and search"
    - "unsupervised learning in a framework of information compression by multiple alignment unification and search"
    - "an alternative to rdf based languages for the representation and processing of ontologies in the semantic web"

Connected through hyperedge HE-2 (induced by source paper "medical diagnosis as pattern recognition in a framework of information compression by multiple alignment unification and search"):
  with members:
    - "syntax parsing and production of natural language in a framework of information compression by multiple alignment unification and search"
    - "probabilistic reasoning as information compression by multiple alignment unification and search an introduction and overview"
    - "unsupervised grammar induction in a framework of information compression by multiple alignment unification and search"
    - "unsupervised learning in a framework of information compression by multiple alignment unification and search"

Connected through hyperedge HE-3 (induced by source paper "unifying computing and cognition the sp theory and its applications"):
  with members:
    - "syntax parsing and production of natural language in a framework of information compression by multiple alignment unification and search"
    - "probabilistic reasoning as information compression by multiple alignment unification and search an introduction and overview"
    - "bootstrapping structure into language alignment based learning"

Connected through hyperedge HE-4 (induced by source paper "neural realisation of the sp theory cell assemblies revisited"):
  with members:
    - "syntax parsing and production of natural language in a framework of information compression by multiple alignment unification and search"
    - "probabilistic reasoning as information compression by multiple alignment unification and search an introduction and overview"
    - "unsupervised grammar induction in a framework of information compression by multiple alignment unification and search"
    - "unsupervised learning in a framework of information compression by multiple alignment unification and search"

Connected through hyperedge HE-5 (induced by source paper "unsupervised learning in a framework of information compression by multiple alignment unification and search"):
  with members:
    - "syntax parsing and production of natural language in a framework of information compression by multiple alignment unification and search"
    - "probabilistic reasoning as information compression by multiple alignment unification and search an introduction and overview"

Connected through hyperedge HE-6 (induced by source paper "an alternative to rdf based languages for the representation and processing of ontologies in the semantic web"):
  with members:
    - "syntax parsing and production of natural language in a framework of information compression by multiple alignment unification and search"
    - "probabilistic reasoning as information compression by multiple alignment unification and search an introduction and overview"

Connected through hyperedge HE-7 (induced by source paper "syntax parsing and production of natural language in a framework of information compression by multiple alignment unification and search"):
  with members:
    - "probabilistic reasoning as information compression by multiple alignment unification and search an introduction and overview"

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)