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: "scads scale independent storage for social computing applications"
  Abstract: Collaborative web applications such as Facebook, Flickr and Yelp present new challenges for storing and querying large amounts of data. As users and developers are focused more on performance than single copy consistency or the ability to perform ad-hoc queries, there exists an opportunity for a highly-scalable system tailored specifically for relaxed consistency and pre-computed queries. The Web 2.0 development model demands the ability to both rapidly deploy new features and automatically scale with the number of users. There have been many successful distributed key-value stores, but so far none provide as rich a query language as SQL. We propose a new architecture, SCADS, that allows the developer to declaratively state application specific consistency requirements, takes advantage of utility computing to provide cost effective scale-up and scale-down, and will use machine learning models to introspectively anticipate performance problems and predict the resource requirements of new queries before execution.

Connected through hyperedge HE-1 (induced by source paper "alvec auto scaling by lotka volterra elastic cloud a qos aware non linear dynamical allocation model"):
  with members:
    - "sustainable cloud computing foundations and future directions"
    - "a comparison of reinforcement learning techniques for fuzzy cloud auto scaling"
    - "qos guaranteed intelligent routing using hybrid pso ga in wireless mesh networks"

Connected through hyperedge HE-2 (induced by source paper "the case for learned index structures"):
  with members:
    - "a model for learned bloom filters and related structures"
    - "a tree a bounded approximate index structure"
    - "outrageously large neural networks the sparsely gated mixture of experts layer"
    - "imagenet training in minutes"
    - "the end of a myth distributed transactions can scale"
    - "google s neural machine translation system bridging the gap between human and machine translation"
    - "tensorflow a system for large scale machine learning"
    - "learning to hash for indexing big data a survey"

Connected through hyperedge HE-3 (induced by source paper "what do shannon type inequalities submodular width and disjunctive datalog have to do with one another"):
  with members:
    - "size bounds and query plans for relational joins"
    - "constraint solving via fractional edge covers"
    - "computing join queries with functional dependencies"
    - "entropy bounds for conjunctive queries with functional dependencies"
    - "faq questions asked frequently"
    - "joins via geometric resolutions worst case and beyond"
    - "aggregation and ordering in factorised databases"
    - "skew strikes back new developments in the theory of join algorithms"

Connected through hyperedge HE-4 (induced by source paper "mdcc multi data center consistency"):
  with members:
    - "piql success tolerant query processing in the cloud"
    - "using paxos to build a scalable consistent and highly available datastore"
    - "a critique of ansi sql isolation levels"

Connected through hyperedge HE-5 (induced by source paper "piql success tolerant query processing in the cloud"):
  with members:
    - "optimal aggregation algorithms for middleware"

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)