human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "smoke fine grained lineage at interactive speed"):
  Abstract: Data lineage describes the relationship between individual input and output data items of a workflow, and has served as an integral ingredient for both traditional (e.g., debugging, auditing, data integration, and security) and emergent (e.g., interactive visualizations, iterative analytics, explanations, and cleaning) applications. The core, long-standing problem that lineage systems need to address---and the main focus of this paper---is to capture the relationships between input and output data items across a workflow with the goal to streamline queries over lineage. Unfortunately, current lineage systems either incur high lineage capture overheads, or lineage query processing costs, or both. As a result, applications, that in principle can express their logic declaratively in lineage terms, resort to hand-tuned implementations. To this end, we introduce Smoke, an in-memory database engine that neither lineage capture overhead nor lineage query processing needs to be compromised. To do so, Smoke introduces tight integration of the lineage capture logic into physical database operators; efficient, write-optimized lineage representations for storage; and optimizations when future lineage queries are known up-front. Our experiments on microbenchmarks and realistic workloads show that Smoke reduces the lineage capture overhead and streamlines lineage queries by multiple orders of magnitude compared to state-of-the-art alternatives. Our experiments on real-world applications highlight that Smoke can meet the latency requirements of interactive visualizations (e.g., <150ms) and outperform hand-written implementations of data profiling primitives.

Includes members:
  Member "holoclean holistic data repairs with probabilistic inference":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "benchmark and survey of automated machine learning frameworks")
  Member "revisiting reuse in main memory database systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "progressive data science potential and challenges")
  Member "afterburner the case for in browser analytics":
    also connected through other hyperedges:
      (none)
  Member "algorithms for provisioning queries and analytics":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "provenance for interactive visualizations")

Question: Please tell me which class the source paper 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)