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: "interacting conceptual spaces i grammatical composition of concepts"
  Abstract: The categorical compositional approach to meaning has been successfully applied in natural language processing, outperforming other models in mainstream empirical language processing tasks. We show how this approach can be generalized to conceptual space models of cognition. In order to do this, first we introduce the category of convex relations as a new setting for categorical compositional semantics, emphasizing the convex structure important to conceptual space applications. We then show how to construct conceptual spaces for various types such as nouns, adjectives and verbs. Finally we show by means of examples how concepts can be systematically combined to establish the meanings of composite phrases from the meanings of their constituent parts. This provides the mathematical underpinnings of a new compositional approach to cognition.

Connected through hyperedge HE-1 (induced by source paper "compositionality for recursive neural networks"):
  with members:
    - "recursive neural networks can learn logical semantics"
    - "the frobenius anatomy of word meanings i subject and object relative pronouns"
    - "distributed representations of words and phrases and their compositionality"
    - "multi step regression learning for compositional distributional semantics"
    - "mathematical foundations for a compositional distributional model of meaning"

Connected through hyperedge HE-2 (induced by source paper "moral dilemmas for artificial intelligence a position paper on an application of compositional quantum cognition"):
  with members:
    - "types of cognition and its implications for future high level cognitive machines"
    - "interacting conceptual spaces"
    - "a compositional explanation of the pet fish phenomenon"
    - "concepts and their dynamics a quantum theoretic modeling of human thought"
    - "crowdsourcing a word emotion association lexicon"
    - "quantum structure in cognition fundamentals and applications"
    - "experimental support for a categorical compositional distributional model of meaning"
    - "mathematical foundations for a compositional distributional model of meaning"

Connected through hyperedge HE-3 (induced by source paper "translating and evolving towards a model of language change in discocat"):
  with members:
    - "sentence entailment in compositional distributional semantics"
    - "loss in translation learning bilingual word mapping with a retrieval criterion"
    - "a generalised quantifier theory of natural language in categorical compositional distributional semantics with bialgebras"
    - "graded entailment for compositional distributional semantics"
    - "open system categorical quantum semantics in natural language processing"
    - "from logical to distributional models"
    - "exploiting similarities among languages for machine translation"
    - "mathematical foundations for a compositional distributional model of meaning"

Connected through hyperedge HE-4 (induced by source paper "towards functorial language games"):
  with members:
    - "a compositional treatment of iterated open games"
    - "compositional game theory"
    - "graded entailment for compositional distributional semantics"
    - "open system categorical quantum semantics in natural language processing"
    - "distributional sentence entailment using density matrices"
    - "from logical to distributional models"
    - "mathematical foundations for a compositional distributional model of meaning"

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.LO(Logic in Computer Science)