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: "the exception that improves the rule"
  Abstract: The database community has developed numerous tools and techniques for data curation and exploration, from declarative languages, to specialized techniques for data repair, and more. Yet, there is currently no consensus on how to best expose these powerful tools to an analyst in a simple, intuitive, and above all, flexible way. Thus, analysts continue to rely on tools such as spreadsheets, imperative languages, and notebook style programming environments like Jupyter for data curation. In this work, we explore the integration of spreadsheets, notebooks, and relational databases. We focus on a key advantage that both spreadsheets and imperative notebook environments have over classical relational databases: ease of exception. By relying on set-at-a-time operations, relational databases sacrifice the ability to easily define singleton operations, exceptions to a normal data processing workflow that affect query processing for a fixed set of explicitly targeted records. In comparison, a spreadsheet user can easily change the formula for just one cell, while a notebook user can add an imperative operation to her notebook that alters an output 'view'. We believe that enabling such idiosyncratic manual transformations in a classical relational database is critical for curation, as curation operations that are easy to declare for individual values can often be extremely challenging to generalize. We explore the challenges of enabling singletons in relational databases, propose a hybrid spreadsheet/relational notebook environment for data curation, and present our vision of Vizier, a system that exposes data curation through such an interface.

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)