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: "graphvista interactive exploration of large graphs"
  Abstract: The potential to gain business insights from graph-structured data through graph analytics is increasingly attracting companies from a variety of industries, ranging from web companies to traditional enterprise businesses. To analyze a graph, a user often executes isolated graph queries using a dedicated interface---a procedural graph programming interface or a declarative graph query language. The results are then returned and displayed using a specific visualization technique. This follows the classical ad-hoc Query$\rightarrow$Result interaction paradigm and often requires multiple query iterations until an interesting aspect in the graph data is identified. This is caused on the one hand by the schema flexibility of graph data and on the other hand by the intricacies of declarative graph query languages. To lower the burden for the user to explore an unknown graph without prior knowledge of a graph query language, visual graph exploration provides an effective and intuitive query interface to navigate through the graph interactively. #R##N#We demonstrate GRAPHVISTA, a graph visualization and exploration tool that can seamlessly combine ad-hoc querying and interactive graph exploration within the same query session. In our demonstration, conference attendees will see GRAPHVISTA running against a large real-world graph data set. They will start by identifying entry points of interest with the help of ad-hoc queries and will then discover the graph interactively through visual graph exploration.

Connected through hyperedge HE-1 (induced by source paper "the ubiquity of large graphs and surprising challenges of graph processing extended survey"):
  with members:
    - "graph based preconditioning conjugate gradient algorithm for n 1 contingency analysis"
    - "g core a core for future graph query languages"
    - "foundations of modern query languages for graph databases"
    - "the gremlin graph traversal machine and language invited talk"
    - "querying knowledge graphs by example entity tuples"
    - "standards for graph algorithm primitives"

Connected through hyperedge HE-2 (induced by source paper "the ubiquity of large graphs and surprising challenges of graph processing"):
  with members:
    - "querying knowledge graphs by example entity tuples"
    - "standards for graph algorithm primitives"

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)