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: "a survey on array storage query languages and systems"
  Abstract: Since scientific investigation is one of the most important providers of massive amounts of ordered data, there is a renewed interest in array data processing in the context of Big Data. To the best of our knowledge, a unified resource that summarizes and analyzes array processing research over its long existence is currently missing. In this survey, we provide a guide for past, present, and future research in array processing. The survey is organized along three main topics. Array storage discusses all the aspects related to array partitioning into chunks. The identification of a reduced set of array operators to form the foundation for an array query language is analyzed across multiple such proposals. Lastly, we survey real systems for array processing. The result is a thorough survey on array data storage and processing that should be consulted by anyone interested in this research topic, independent of experience level. The survey is not complete though. We greatly appreciate pointers towards any work we might have forgotten to mention.

Connected through hyperedge HE-1 (induced by source paper "towards scalable dataframe systems"):
  with members:
    - "verdictdb universalizing approximate query processing"
    - "helix holistic optimization for accelerating iterative machine learning"
    - "ray a distributed framework for emerging ai applications"
    - "adaptive sampling for rapidly matching histograms"
    - "laradb a minimalist kernel for linear and relational algebra computation"
    - "towards a holistic integration of spreadsheets with databases a scalable storage engine for presentational data management"
    - "lara a key value algebra underlying arrays and relations"
    - "visualization aware sampling for very large databases"

Connected through hyperedge HE-2 (induced by source paper "distributed caching for complex querying of raw arrays"):
  with members:
    - "stochastic gradient descent on highly parallel architectures"
    - "arraybridge interweaving declarative array processing with high performance computing"
    - "tensorflow a system for large scale machine learning"

Connected through hyperedge HE-3 (induced by source paper "on the expressive power of query languages for matrices"):
  with members:
    - "on matrices and k relations"
    - "on the expressive power of linear algebra on graphs"
    - "laradb a minimalist kernel for linear and relational algebra computation"
    - "embedding tarskian semantics in vector spaces"
    - "towards linear algebra over normalized data"
    - "a linear algebraic approach to datalog evaluation"
    - "reachability is in dynfo"
    - "rank logic is dead long live rank logic"

Connected through hyperedge HE-4 (induced by source paper "time series management systems a survey"):
  with members:
    - "the madlib analytics library or mad skills the sql"
    - "tsds high performance merge subset and filter software for time series like data"

Connected through hyperedge HE-5 (induced by source paper "arraybridge interweaving declarative array processing with high performance computing"):
  with members:
    - "principles of dataset versioning exploring the recreation storage tradeoff"
    - "datahub collaborative data science dataset version management at scale"

Connected through hyperedge HE-6 (induced by source paper "formal representation of the ss db benchmark and experimental evaluation in extascid"):
  with members:
    - "riot i o efficient numerical computing without sql"

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)