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: "forkbase an efficient storage engine for blockchain and forkable applications"
  Abstract: Existing data storage systems offer a wide range of functionalities to accommodate an equally diverse range of applications. However, new classes of applications have emerged, e.g., blockchain and collaborative analytics, featuring data versioning, fork semantics, tamper-evidence or any combination thereof. They present new opportunities for storage systems to efficiently support such applications by embedding the above requirements into the storage. #R##N#In this paper, we present ForkBase, a storage engine specifically designed to provide efficient support for blockchain and forkable applications. By integrating the core application properties into the storage, ForkBase not only delivers high performance but also reduces development effort. Data in ForkBase is multi-versioned, and each version uniquely identifies the data content and its history. Two variants of fork semantics are supported in ForkBase to facilitate any collaboration workflows. A novel index structure is introduced to efficiently identify and eliminate duplicate content across data objects. Consequently, ForkBase is not only efficient in performance, but also in space requirement. We demonstrate the performance of ForkBase using three applications: a blockchain platform, a wiki engine and a collaborative analytics application. We conduct extensive experimental evaluation of these applications against respective state-of-the-art system. The results show that ForkBase achieves superior performance while significantly lowering the development cost.

Connected through hyperedge HE-1 (induced by source paper "a blueprint for interoperable blockchains"):
  with members:
    - "cross chain deals and adversarial commerce"
    - "towards scaling blockchain systems via sharding"
    - "atomic cross chain swaps"
    - "pdfs practical data feed service for smart contracts"
    - "securify practical security analysis of smart contracts"
    - "sprites and state channels payment networks that go faster than lightning"
    - "adding concurrency to smart contracts"
    - "blockbench a framework for analyzing private blockchains"

Connected through hyperedge HE-2 (induced by source paper "panda facilitating usable ai development"):
  with members:
    - "rafiki machine learning as an analytics service system"
    - "medical concept embedding with time aware attention"
    - "deep forest"
    - "progressive neural architecture search"
    - "ease ml towards multi tenant resource sharing for machine learning workloads"
    - "the case for learned index structures"
    - "thoracic disease identification and localization with limited supervision"
    - "scaling sgd batch size to 32k for imagenet training"

Connected through hyperedge HE-3 (induced by source paper "chain of trust can trusted hardware help scaling blockchains"):
  with members:
    - "decentralization in bitcoin and ethereum networks"
    - "sprites and state channels payment networks that go faster than lightning"
    - "chainspace a sharded smart contracts platform"
    - "adding concurrency to smart contracts"
    - "blockbench a framework for analyzing private blockchains"
    - "untangling blockchain a data processing view of blockchain systems"
    - "enhancing bitcoin security and performance with strong consistency via collective signing"
    - "algorand the efficient and democratic ledger"

Connected through hyperedge HE-4 (induced by source paper "towards scaling blockchain systems via sharding"):
  with members:
    - "sprites and state channels payment networks that go faster than lightning"
    - "chainspace a sharded smart contracts platform"
    - "adding concurrency to smart contracts"
    - "blockbench a framework for analyzing private blockchains"
    - "untangling blockchain a data processing view of blockchain systems"
    - "enhancing bitcoin security and performance with strong consistency via collective signing"
    - "algorand the efficient and democratic ledger"
    - "xft practical fault tolerance beyond crashes"

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)