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: "estimating the cardinality of conjunctive queries over rdf data using graph summarisation"
  Abstract: Accurately estimating the cardinality (i.e., the number of answers) of conjunctive queries is a core problem in data management. Common solutions to this problem are susceptible to high estimation errors that compound exponentially with the number of joins; hence, existing techniques can be inaccurate in data models such as RDF where queries are navigational and often involve many (self-)joins. In this paper we present a new technique for estimating the cardinality of conjunctive queries in RDF. We use a summary of an RDF graph as a synopsis that we interpret using a possible world semantics. We formalise the estimation problem as computing the expectation of query cardinality over all RDF graphs represented by the summary, and we present a closed-form formula for computing the expectation of arbitrary queries. We also discuss approaches to RDF graph summarisation. Finally, we show empirically that our cardinality technique is more accurate and more consistent, often by orders of magnitude, than several state-of-the-art approaches.

Connected through hyperedge HE-1 (induced by source paper "functorial question answering"):
  with members:
    - "relating structure and power comonadic semantics for computational resources"
    - "graphical conjunctive queries"
    - "towards compositional distributional discourse analysis"
    - "a dichotomy theorem for nonuniform csps"
    - "knowledge representation in bicategories of relations"
    - "quantum algorithms for compositional natural language processing"
    - "the frobenius anatomy of word meanings i subject and object relative pronouns"
    - "from logical to distributional models"

Connected through hyperedge HE-2 (induced by source paper "approximate evaluation of label constrained reachability queries"):
  with members:
    - "gmark schema driven generation of graphs and queries"
    - "g core a core for future graph query languages"
    - "an analytical study of large sparql query logs"
    - "the ubiquity of large graphs and surprising challenges of graph processing"
    - "foundations of modern query languages for graph databases"
    - "graph summarization methods and applications a survey"
    - "blinkdb queries with bounded errors and bounded response times on very large data"

Connected through hyperedge HE-3 (induced by source paper "towards compositional distributional discourse analysis"):
  with members:
    - "question answering with grammatically interpretable representations"
    - "the frobenius anatomy of word meanings ii possessive relative pronouns"
    - "a quantum teleportation inspired algorithm produces sentence meaning from word meaning and grammatical structure 15"
    - "the frobenius anatomy of word meanings i subject and object relative pronouns"
    - "experimental support for a categorical compositional distributional model of meaning"
    - "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.DB(Databases)