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: "principles of dataset versioning exploring the recreation storage tradeoff"
  Abstract: The relative ease of collaborative data science and analysis has led to a proliferation of many thousands or millions of $versions$ of the same datasets in many scientific and commercial domains, acquired or constructed at various stages of data analysis across many users, and often over long periods of time. Managing, storing, and recreating these dataset versions is a non-trivial task. The fundamental challenge here is the $storage-recreation\;trade-off$: the more storage we use, the faster it is to recreate or retrieve versions, while the less storage we use, the slower it is to recreate or retrieve versions. Despite the fundamental nature of this problem, there has been a surprisingly little amount of work on it. In this paper, we study this trade-off in a principled manner: we formulate six problems under various settings, trading off these quantities in various ways, demonstrate that most of the problems are intractable, and propose a suite of inexpensive heuristics drawing from techniques in delay-constrained scheduling, and spanning tree literature, to solve these problems. We have built a prototype version management system, that aims to serve as a foundation to our DATAHUB system for facilitating collaborative data science. We demonstrate, via extensive experiments, that our proposed heuristics provide efficient solutions in practical dataset versioning scenarios.

Connected through hyperedge HE-1 (induced by source paper "dfs a dataset file system for data discovering users"):
  with members:
    - "mnasnet platform aware neural architecture search for mobile"
    - "progressive neural architecture search"
    - "neural architecture search with reinforcement learning"

Connected through hyperedge HE-2 (induced by source paper "a survey on data collection for machine learning a big data ai integration perspective"):
  with members:
    - "data cleaning for accurate fair and robust models a big data ai integration approach"
    - "the gan landscape losses architectures regularization and normalization"
    - "adversarial example generation with syntactically controlled paraphrase networks"
    - "snorkel drybell a case study in deploying weak supervision at industrial scale"
    - "data synthesis based on generative adversarial networks"
    - "quality control in crowdsourcing a survey of quality attributes assessment techniques and assurance actions"
    - "a survey on deep transfer learning"
    - "learning based video motion magnification"

Connected through hyperedge HE-3 (induced by source paper "forkbase an efficient storage engine for blockchain and forkable applications"):
  with members:
    - "blocksci design and applications of a blockchain analysis platform"
    - "ustore a distributed storage with rich semantics"
    - "untangling blockchain a data processing view of blockchain systems"
    - "datahub collaborative data science dataset version management at scale"
    - "efficient snapshot retrieval over historical graph data"

Connected through hyperedge HE-4 (induced by source paper "rstore a distributed multi version document store"):
  with members:
    - "data placement and replica selection for improving co location in distributed environments"
    - "efficient snapshot retrieval over historical graph data"

Connected through hyperedge HE-5 (induced by source paper "towards a theory of data diff optimal synthesis of succinct data modification scripts"):
  with members:
    - "learning semantic string transformations from examples"

Connected through hyperedge HE-6 (induced by source paper "orpheusdb bolt on versioning for relational databases"):
  with members:
    - "datahub collaborative data science dataset version management at scale"
    - "nscale neighborhood centric large scale graph analytics in the cloud"
    - "dbtoaster higher order delta processing for dynamic frequently fresh views"

Connected through hyperedge HE-7 (induced by source paper "arraybridge interweaving declarative array processing with high performance computing"):
  with members:
    - "datahub collaborative data science dataset version management at scale"
    - "a survey on array storage query languages and systems"

Connected through hyperedge HE-8 (induced by source paper "towards a unified query language for provenance and versioning"):
  with members:
    - "datahub collaborative data science dataset version management at scale"

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)