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: "compositional distributional semantics with compact closed categories and frobenius algebras"
  Abstract: The provision of compositionality in distributional models of meaning, where a word is represented as a vector of co-occurrence counts with every other word in the vocabulary, offers a solution to the fact that no text corpus, regardless of its size, is capable of providing reliable co-occurrence statistics for anything but very short text constituents. The purpose of a compositional distributional model is to provide a function that composes the vectors for the words within a sentence, in order to create a vectorial representation that re ects its meaning. Using the abstract mathematical framework of category theory, Coecke, Sadrzadeh and Clark showed that this function can directly depend on the grammatical structure of the sentence, providing an elegant mathematical counterpart of the formal semantics view. The framework is general and compositional but stays abstract to a large extent.   This thesis contributes to ongoing research related to the above categorical model in three ways: Firstly, I propose a concrete instantiation of the abstract framework based on Frobenius algebras (joint work with Sadrzadeh). The theory improves shortcomings of previous proposals, extends the coverage of the language, and is supported by experimental work that improves existing results. The proposed framework describes a new class of compositional models thatfind intuitive interpretations for a number of linguistic phenomena.   Secondly, I propose and evaluate in practice a new compositional methodology which explicitly deals with the different levels of lexical ambiguity (joint work with Pulman). A concrete algorithm is presented, based on the separation of vector disambiguation from composition in an explicit prior step. Extensive experimental work shows that the proposed methodology indeed results in more accurate composite representations for the framework of Coecke et al. in particular and every other class of compositional models in general.   As a last contribution, I formalize the explicit treatment of lexical ambiguity in the context of the categorical framework by resorting to categorical quantum mechanics (joint work with Coecke). In the proposed extension, the concept of a distributional vector is replaced with that of a density matrix, which compactly represents a probability distribution over the potential different meanings of the specific word. Composition takes the form of quantum measurements, leading to interesting analogies between quantum physics and linguistics.

Connected through hyperedge HE-1 (induced by source paper "the mathematics of text structure"):
  with members:
    - "compositionality for recursive neural networks"
    - "static and dynamic vector semantics for lambda calculus models of natural language"
    - "towards compositional distributional discourse analysis"
    - "classical copying versus quantum entanglement in natural language the case of vp ellipsis"
    - "internal wiring of cartesian verbs and prepositions"
    - "from quantum foundations via natural language meaning to a theory of everything"
    - "the frobenius anatomy of word meanings ii possessive relative pronouns"
    - "coordination in categorical compositional distributional semantics"

Connected through hyperedge HE-2 (induced by source paper "sentence entailment in compositional distributional semantics"):
  with members:
    - "a generalised quantifier theory of natural language in categorical compositional distributional semantics with bialgebras"
    - "the frobenius anatomy of word meanings ii possessive relative pronouns"
    - "coordination in categorical compositional distributional semantics"
    - "graded entailment for compositional distributional semantics"
    - "a frobenius model of information structure in categorical compositional distributional semantics"
    - "open system categorical quantum semantics in natural language processing"
    - "distributional sentence entailment using density matrices"
    - "evaluating neural word representations in tensor based compositional settings"

Connected through hyperedge HE-3 (induced by source paper "exploring semantic incrementality with dynamic syntax and vector space semantics"):
  with members:
    - "bootstrapping incremental dialogue systems from minimal data the generalisation power of dialogue grammars"
    - "distributional inclusion hypothesis for tensor based composition"
    - "mathematical foundations for a compositional distributional model of meaning"

Connected through hyperedge HE-4 (induced by source paper "dependencies formalising semantic catenae for information retrieval"):
  with members:
    - "fixed versus dynamic co occurrence windows in textrank term weights for information retrieval"
    - "preliminary experiments using subjective logic for the polyrepresentation of information needs"
    - "rhetorical relations for information retrieval"
    - "time series adaptive estimation of vaccination uptake using web search queries"
    - "part of speech based term weighting for information retrieval"
    - "learning to generate compositional color descriptions"
    - "adaptive distributional extensions to dfr ranking"
    - "exploiting the bipartite structure of entity grids for document coherence and retrieval"

Connected through hyperedge HE-5 (induced by source paper "ambiguity and incomplete information in categorical models of language"):
  with members:
    - "a graph theoretic perspective on cpm rel"
    - "open system categorical quantum semantics in natural language processing"
    - "mathematical foundations for a compositional distributional model of meaning"
    - "monads for natural language semantics"

Connected through hyperedge HE-6 (induced by source paper "a generalised quantifier theory of natural language in categorical compositional distributional semantics with bialgebras"):
  with members:
    - "the frobenius anatomy of word meanings ii possessive relative pronouns"
    - "resolving lexical ambiguity in tensor regression models of meaning"
    - "evaluating neural word representations in tensor based compositional settings"
    - "reasoning about meaning in natural language with compact closed categories and frobenius algebras"
    - "the frobenius anatomy of word meanings i subject and object relative pronouns"
    - "multi step regression learning for compositional distributional semantics"
    - "experimental support for a categorical compositional distributional model of meaning"
    - "mathematical foundations for a compositional distributional model of meaning"

Connected through hyperedge HE-7 (induced by source paper "quantum algorithms for compositional natural language processing"):
  with members:
    - "graded entailment for compositional distributional semantics"
    - "open system categorical quantum semantics in natural language processing"
    - "a quantum teleportation inspired algorithm produces sentence meaning from word meaning and grammatical structure 15"
    - "category theoretic quantitative compositional distributional models of natural language semantics"
    - "learning type driven tensor based meaning representations"
    - "experimental support for a categorical compositional distributional model of meaning"
    - "mathematical foundations for a compositional distributional model of meaning"

Connected through hyperedge HE-8 (induced by source paper "coordination in categorical compositional distributional semantics"):
  with members:
    - "the frobenius anatomy of word meanings ii possessive relative pronouns"
    - "a frobenius model of information structure in categorical compositional distributional semantics"
    - "a compositional explanation of the pet fish phenomenon"
    - "open system categorical quantum semantics in natural language processing"
    - "the frobenius anatomy of word meanings i subject and object relative pronouns"
    - "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.CL(Computation and Language)