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: "ustore a distributed storage with rich semantics"
  Abstract: Today's storage systems expose abstractions which are either too low-level (e.g., key-value store, raw-block store) that they require developers to re-invent the wheels, or too high-level (e.g., relational databases, Git) that they lack generality to support many classes of applications. In this work, we propose and implement a general distributed data storage system, called UStore, which has rich semantics. UStore delivers three key properties, namely immutability, sharing and security, which unify and add values to many classes of today's applications, and which also open the door for new applications. By keeping the core properties within the storage, UStore helps reduce application development efforts while offering high performance at hand. The storage embraces current hardware trends as key enablers. It is built around a data-structure similar to that of Git, a popular source code versioning system, but it also synthesizes many designs from distributed systems and databases. Our current implementation of UStore has better performance than general in-memory key-value storage systems, especially for version scan operations. We port and evaluate four applications on top of UStore: a Git-like application, a collaborative data science application, a transaction management application, and a blockchain application. We demonstrate that UStore enables faster development and the UStore-backed applications can have better performance than the existing implementations.

Connected through hyperedge HE-1 (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"
    - "forkbase an efficient storage engine for blockchain and forkable applications"
    - "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"

Connected through hyperedge HE-2 (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"
    - "untangling blockchain a data processing view of blockchain systems"
    - "principles of dataset versioning exploring the recreation storage tradeoff"
    - "datahub collaborative data science dataset version management at scale"
    - "efficient snapshot retrieval over historical graph data"

Connected through hyperedge HE-3 (induced by source paper "a blockchain database application platform"):
  with members:
    - "untangling blockchain a data processing view of blockchain systems"

Connected through hyperedge HE-4 (induced by source paper "untangling blockchain a data processing view of blockchain systems"):
  with members:
    - "enhancing bitcoin security and performance with strong consistency via collective signing"
    - "bitcoin ng a scalable blockchain protocol"
    - "keeping authorities honest or bust with decentralized witness cosigning"
    - "a first look at the usability of bitcoin key management"
    - "majority is not enough bitcoin mining is vulnerable"

Connected through hyperedge HE-5 (induced by source paper "blockbench a framework for analyzing private blockchains"):
  with members:
    - "enhancing bitcoin security and performance with strong consistency via collective signing"
    - "hijacking bitcoin large scale network attacks on cryptocurrencies"
    - "bitcoin ng a scalable blockchain protocol"
    - "majority is not enough bitcoin mining is vulnerable"

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)