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: "mimir bringing ctables into practice"
  Abstract: The present state of the art in analytics requires high upfront investment of human effort and computational resources to curate datasets, even before the first query is posed. So-called pay-as-you-go data curation techniques allow these high costs to be spread out, first by enabling queries over uncertain and incomplete data, and then by assessing the quality of the query results. We describe the design of a system, called Mimir, around a recently introduced class of probabilistic pay-as-you-go data cleaning operators called Lenses. Mimir wraps around any deterministic database engine using JDBC, extending it with support for probabilistic query processing. Queries processed through Mimir produce uncertainty-annotated result cursors that allow client applications to quickly assess result quality and provenance. We also present a GUI that provides analysts with an interactive tool for exploring the uncertainty exposed by the system. Finally, we present optimizations that make Lenses scalable, and validate this claim through experimental evidence.

Connected through hyperedge HE-1 (induced by source paper "uncertainty annotated databases a lightweight approach for approximating certain answers extended version"):
  with members:
    - "dissociation and propagation for approximate lifted inference with standard relational database management systems"
    - "a unified approach to ranking in probabilistic databases"
    - "fast and simple relational processing of uncertain data"
    - "the dichotomy of conjunctive queries on probabilistic structures"

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)