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: "syntax parsing and production of natural language in a framework of information compression by multiple alignment unification and search"
  Abstract: This article introduces the idea that "information compression by multiple alignment, unification and search" (ICMAUS) provides a framework within which natural language syntax may be represented in a simple format and the parsing and production of natural language may be performed in a transparent manner. #R##N#The ICMAUS concepts are embodied in a software model, SP61. The organisation and operation of the model are described and a simple example is presented showing how the model can achieve parsing of natural language. #R##N#Notwithstanding the apparent paradox of 'decompression by compression', the ICMAUS framework, without any modification, can produce a sentence by decoding a compressed code for the sentence. This is illustrated with output from the SP61 model. #R##N#The article includes four other examples - one of the parsing of a sentence in French and three from the domain of English auxiliary verbs. These examples show how the ICMAUS framework and the SP61 model can accommodate 'context sensitive' features of syntax in a relatively simple and direct manner.

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"
    - "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"
    - "computing as information compression by multiple alignment unification and search"

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:
    - "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"
    - "computing as 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:
    - "probabilistic reasoning as information compression by multiple alignment unification and search an introduction and overview"
    - "computing as information compression by multiple alignment unification and search"
    - "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:
    - "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"
    - "computing as information compression by multiple alignment unification and search"

Connected through hyperedge HE-5 (induced by source paper "unsupervised grammar induction in a framework of information compression by multiple alignment unification and search"):
  with members:
    - "unsupervised learning in a framework of information compression by multiple alignment unification and search"
    - "bootstrapping structure into language alignment based learning"

Connected through hyperedge HE-6 (induced by source paper "unsupervised learning 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"
    - "computing as information compression by multiple alignment unification and search"

Connected through hyperedge HE-7 (induced by source paper "an alternative to rdf based languages for the representation and processing of ontologies in the semantic web"):
  with members:
    - "probabilistic reasoning as information compression by multiple alignment unification and search an introduction and overview"
    - "computing as information compression by multiple alignment unification and search"

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)