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: "provgen generating synthetic prov graphs with predictable structure"
  Abstract: This paper introduces provGen, a generator aimed at producing large synthetic provenance graphs with predictable properties and of arbitrary size. Synthetic provenance graphs serve two main purposes. Firstly, they provide a variety of controlled workloads that can be used to test storage and query capabilities of provenance management systems at scale. Secondly, they provide challenging testbeds for experimenting with graph algorithms for provenance analytics, an area of increasing research interest. provGen produces PROV graphs and stores them in a graph DBMS (Neo4J). A key feature is to let users control the relationship makeup and topological features of the graph, by providing a seed provenance pattern along with a set of constraints, expressed using a custom Domain Specific Language. We also propose a simple method for evaluating the quality of the generated graphs, by measuring how realistically they simulate the structure of real-world patterns.

Connected through hyperedge HE-1 (induced by source paper "loom query aware partitioning of online graphs"):
  with members:
    - "taper query aware partition enhancement for large heterogenous graphs"
    - "a selectivity based approach to continuous pattern detection in streaming graphs"
    - "query workload based rdf graph fragmentation and allocation"
    - "practical graph isomorphism ii"
    - "pt scotch a tool for efficient parallel graph ordering"

Connected through hyperedge HE-2 (induced by source paper "the lifecycle of provenance metadata and its associated challenges and opportunities"):
  with members:
    - "provenance and data differencing for workflow reproducibility analysis"
    - "provabs model policy and tooling for abstracting prov graphs"
    - "transitive credit as a means to address social and technological concerns stemming from citation and attribution of digital products"
    - "putting lipstick on pig enabling database style workflow provenance"

Connected through hyperedge HE-3 (induced by source paper "taper query aware partition enhancement for large heterogenous graphs"):
  with members:
    - "multi scale community detection using stability optimisation within greedy algorithms"
    - "the graph traversal pattern"

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)